{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from scipy.io import loadmat\n",
    "from sklearn.metrics import (adjusted_rand_score as ari,\n",
    "                             normalized_mutual_info_score as nmi)\n",
    "\n",
    "from coclust.coclustering import (CoclustMod, CoclustSpecMod, CoclustInfo)\n",
    "from coclust.io.data_loading import load_doc_term_data\n",
    "from coclust.evaluation.internal import best_modularity_partition\n",
    "from coclust.evaluation.external import accuracy\n",
    "from coclust.io.notebook import(input_with_default_int, input_with_default_str)\n",
    "from coclust.visualization import (plot_max_modularities, \n",
    "                                   plot_intermediate_modularities,\n",
    "                                   plot_cluster_top_terms, \n",
    "                                   get_term_graph, \n",
    "                                   plot_cluster_sizes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Co-occurence file path: [default: ../datasets/classic3_coclustFormat.mat] \n"
     ]
    }
   ],
   "source": [
    "# ** Get best co-clustering with the CoclustMod approach **\n",
    "\n",
    "# [Co-clustering by direct maximization of graph modularity]\n",
    "\n",
    "# Provide a co-occurence file path\n",
    "# Exp: \"../datasets/classic3.mat\"\n",
    "# Exp: \"../datasets/classic3.csv\"\n",
    "file_path = input_with_default_str('Co-occurence file path', \"../datasets/classic3_coclustFormat.mat\")\n",
    "\n",
    "# Load the given co-occurence matrix and associated term labels\n",
    "doc_term_data = load_doc_term_data(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum number of clusters: [default: 2] \n",
      "Maximum number of clusters: [default: 9] \n",
      "Number of random initialization per cluster number: [default: 1] \n",
      "Computing coclust modularity for a range of cluster numbers =\n",
      " 2 ...\n",
      " 3 ...\n",
      " 4 ...\n",
      " 5 ...\n",
      " 6 ...\n",
      " 7 ...\n",
      " 8 ...\n",
      " 9 ...\n",
      " All done !\n"
     ]
    }
   ],
   "source": [
    "# ** Compute the final coClust modularity on a range of number of clusters **\n",
    "\n",
    "# -- range of number of clusters\n",
    "# ---- get min\n",
    "min_cluster_nbr = input_with_default_int('Minimum number of clusters', 2)\n",
    "max_cluster_nbr = input_with_default_int('Maximum number of clusters', 9)\n",
    "range_n_clusters = range(min_cluster_nbr, (max_cluster_nbr+1))\n",
    "\n",
    "# -- Number of random initialization per cluster number\n",
    "n_rand_init = input_with_default_int('Number of random initialization per cluster number', 1)\n",
    "\n",
    "# --  max modularity for all models\n",
    "best_coclustMod_model, all_max_modularities = best_modularity_partition(doc_term_data['doc_term_matrix'], \n",
    "                                                                        range_n_clusters, n_rand_init)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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f4cGDB5g/f35xNoMxxhhjRVAqkpF9+/bBz88P3t7eqFatGoKCgmBqaorQ0NA8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\nPobxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a790d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ** Plot all final modularities **\n",
    "plot_max_modularities(all_max_modularities, range_n_clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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PPoJabRW7TUQ1UHVNDCzRFVTqC4CsTCAjvfBfZjpkZjqQkWZ4jYx0yHt/H93+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\nMiIiIiK2UhkRERERW6mMiIiIiK1URkRERMRWKiMiIiJiK5U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X8uabb/LQQw/Rs2dPEhMT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\nnj2Wl1QlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10708a9d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ** Plot intermediate modularities for the best CoClust final modularity **\n",
    "plot_intermediate_modularities(best_coclustMod_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of top terms: [default: 10] \n"
     ]
    },
    {
     "data": {
      "image/png": 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B3VxKSkqwbt062NnZISgoCIIgPND1CxcuRJ8+fdCuXTvDsR07diAtLQ0DBw6ssb/9+/ej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Fq1aqSmpnLmzP/KbFJSUkhISOD999/nzJkzvPLKK6xatYp77733in1///33fPXVV7zwwguEhoYS\nHR3NrFmz6NChg0u7devWMW7cOOrUqUN2djY7d+5k2rRpPPPMMzRu3Jhjx47x1ltvUbFiRdq3b+/S\n/yuvvIKvry9Tpkxh9uzZvPLKK+5LjoiIiIhIKeX2sqiMjAx+/PFHRowYQbVq1YALqy8GBwc723h5\neXH//ffj5eWFzWajdevW7Nu3r1D9b9y4kfDwcOrWrYvZbKZr166Ehobma9e1a1fq1KkDgNVqZeXK\nlfTq1YvGjRsDUKtWLXr27MmGDRtcjhswYAD+/v54eXnRtWvXQsclIiIiIlLWuX3mIikpCYDq1atf\nsk2lSpUwm/83rvHx8SErK6tQ/aekpHDbbbe5bCtoSfMqVaq4/HzixAm2b9/O6tWrndscDke+YwMC\nAlziOnfuXKHiEhG5FmaLBbvdVtxhXDdvb2/sdntxh1HqKc+eo1x7hvJc9K70ICV3c/vg4uKb9RMn\nTrjMVrhL5cqVSUxMdNmWlJREzZo1Xbb9NZE2m41OnTrRt29ft8ckInKtHHl5pWKRP7vdXiquo6RT\nnj1HufYM5bnoeXt7F/hBfFFxe1mUv78/7dq1IzIykpMnTwKQmprKkSNH3NJ/p06diIqKYt++fTgc\nDjZs2MCBAweueNztt9/OqlWr2LFjBw6HA4fDwdGjR9m1a5db4hIRERERKeuK5IbukSNHsmTJEt58\n803S09MJCAjggQceKPRMxuWmbzp06EBqaiqTJ0/m3LlztGnThr///e9XPD4sLAyr1crixYv5448/\nMJlMVK9enbvuuuvqLk5ERERERApkMgxDS8OKiyHzY7WInoiHRPZrQJDPjb+InkobPEN59hzl2jOU\n56J3w5dFiYiIiIhI2VQkZVFyY3s1PISs7JziDqNUM1ssOLRyvEeU9Fz7epsBTSCLiEjpoMGF5BNQ\nzoSf+cYv0yjJ7HabpoE9pOTnWgMLEREpPVQWJSIiIiIibqGZC8nn1HmDrGx9mlqUUhLScOQpx55Q\nVLn29TZTwaLfoYiIyJ9d1eAiIiKCJk2a0L9//6KKR0qA16IO6WlRIlcQ2a8BFSwqHxQREfkzlUWJ\niIiIiIhbFOvgwjAMHA5HcYYgIiIiIiJuctX3XGRmZjJ16lS2bNlChQoVuPfee+nWrZtzf1xcHEuX\nLiUxMRG73c4dd9xB165dAUhKSmLMmDE8+uijrFy5koSEBCZOnMiKFSvIzc2lXLlybN68GavVypAh\nQ6hduzYfffQRx44dIzQ0lCeeeIKAgAAAzpw5w4IFC/j1119xOBw0atSIYcOGYbfbAZgxYwa5ubn4\n+fkRExODl5cX3bp1Y8CAAc5Y//jjDz7++GP279+Pl5cXrVq1YujQoZQrV+66kioiIiIiUhZd9cxF\ndHQ03bt3Z/78+QwdOpTZs2eTlJQEwN69e5kyZQoDBgxgzpw5/POf/2TBggXExsa69PHdd9/x8ssv\ns2DBAqpVqwZAbGwsYWFhzJkzh/79+zNz5kw+++wzxo4dy6xZszAMg8WLFzv7+OCDD0hLS2Py5Ml8\n8MEHWK1W3nnnHf684HhsbCxNmjQhMjKSp59+mmXLlrF7924ATp8+zYQJE2jRogX/+c9/mDRpEgkJ\nCcyfP//qsygiIiIiIlc/uLjtttto1KgRAH//+9/x9fXl4MGDAGzYsIGwsDBuvfVWTCYTjRo1Ijw8\nnKioKJc+BgwYQEBAAGazGS+vC5MnjRs3pmXLlphMJjp16kR2djbt27fHbrdjtVpp06YN+/fvB+DU\nqVNs27aNYcOG4efnh4+PDw899BBHjhxxtgFo1KgRbdq0wWQy0aBBA0JCQti3bx8AGzdupGbNmvTq\n1QuLxYKfnx8DBw5k48aNLgMUEREREREpnKsui7pYdnSRj48PWVlZAKSkpFC7dm2X/dWqVWPbtm0u\n24KCgvL1a7PZnN9brdZ828qVK+dyHoAqVao49/v6+lKxYkWSk5OpW7cugLOE6s+xnjt3DoCTJ0/y\n+++/M3z4cOd+wzAwm82kpaXlO1ZE5M/MFgt2u+3KDcsIb2/vfH8fxP2UZ89Rrj1DeS56JpNnn2zo\n1nUuKleuTGJiosu2kydPEhgY6LLNbL6++8gv9peYmEiNGjWAC/eCnD59Ot+5LsVms9GkSRNeeuml\n64pFRMomR15eCV/527Psdrvy4QHKs+co156hPBc9b2/vAj/YLypufVpUly5diIuLY+vWrTgcDnbv\n3s369esJDw9352mw2Wy0aNGC+fPnc/r0ac6dO8ecOXMIDg6mTp06heqjc+fOHDhwgLVr15KdnQ1A\ncnIycXFxbo1VRERERKSsuO6Ziz9PtdSrV48nn3ySRYsWMXXqVAICAhg6dCitW7e+3tPk8/jjj7Ng\nwQKeeeYZHA4HDRs25Nlnny301E9gYCCvv/46CxcuZOnSpWRnZ2O322nXrh1hYWFuj1dEREREpLQz\nGbp7Wf5iyPxYrdAtcgWR/RoQ5KMVui9SaYNnKM+eo1x7hvJc9G7osigRERERESm73HpDt5QOr4aH\nkJWdU9xhlGpmiwVHXl5xh1EmFFWufb3NgCZ+RURE/kyDC8knoJwJP7PKPYqS3W7TNLCHFF2uNbAQ\nERH5K5VFiYiIiIiIW2hwISIiIiIibqHBhYiIiIiIuIUGFyIiIiIi4hYaXIiIiIiIiFvoaVGSj5eX\nXhZFzWQy4e3tXdxhlAnKtWcoz56hPHuOcu0ZynPR8/T7Oq3QLSIiIiIibqGyKHGxYsWK4g6hTJg3\nb15xh1BmKNeeoTx7hvLsOcq1ZyjPnuHJ93caXIiLXbt2FXcIZUJCQkJxh1BmKNeeoTx7hvLsOcq1\nZyjPnuHJ93caXIiIiIiIiFtocCEiIiIiIm6hwYWIiIiIiLiFZcKECROKOwgpWYKDg4s7hDJBefYc\n5dozlGfPUJ49R7n2DOXZMzyVZz2KVkRERERE3EJlUSIiIiIi4hYaXIiIiIiIiFtocCEiIiIiIm6h\nwYWIiIiIiLiFV3EHICXDf//7X77++mvS0tIICQlh+PDh1K1bt7jDuqHs2rWLFStWcODAAdLS0hg3\nbhy33nqrS5vFixezfv16zp49S4MGDXjkkUeoVq2ac/+ZM2eYM2cOW7ZswWw206ZNG4YNG4aPj4+n\nL6fE+vLLL4mNjeX48eNYrVbq16/PAw88QI0aNZxtcnJymD9/Pj/++CM5OTk0b96cf/7zn1SqVMnZ\nJjk5mVmzZhEfH4+Pjw+dOnXi/vvvx2zWZy4Aa9asYe3atSQmJgJw00030b9/f1q0aAEox0Xlyy+/\n5LPPPuP222/nwQcfBJRrd1myZAlLly512VajRg3ee+89QHl2p9TUVD799FO2bdvG+fPnqV69Oo89\n9hihoaHONvp7eH1Gjx5NcnJyvu09e/bkoYceKtbXsx5FK2zatInIyEj+8Y9/MGjQIBITE1m4cCFd\nu3alXLlyxR3eDeOPP/4gLy+Prl278uOPP9KuXTuXN7zLly9n5cqVjBw5krvuuovdu3fzzTff0KNH\nD+c/5P/7v/8jKSmJp59+mrZt27J69WoOHjxImzZtiuuySpzly5fTtWtX+vfvT8eOHfntt9/45ptv\n6N69OxaLBYA5c+awbds2nnzySbp3786mTZvYvHkzXbp0AcDhcPDqq6/i4+PDU089RdOmTfn888/J\nysrib3/7W3FeXomRnp5O8+bNueeee+jevTuZmZnMmTOHNm3a4O/vrxwXgX379rFo0SKCgoKoUqWK\ncyCnXLtHfHw8p0+fZvLkydx5553ceeedhIeHY7VaAeXZXc6ePcuLL75I9erVGT58OHfddRehoaHY\n7XYqVKgA6O+hO3Ts2JE+ffo4X8vNmzfnu+++Y+jQoQQFBRXv69mQMu/FF1805syZ4/zZ4XAYjz76\nqLF8+fJijOrGNnDgQCMuLs5l24gRI4yvv/7a+fPZs2eN+++/34iJiTEMwzCOHj1qDBw40Dhw4ICz\nzS+//GIMGjTIOHXqlGcCvwGlp6cbAwcONHbt2mUYxoW83nfffcZPP/3kbPPHH38YAwcONPbu3WsY\nhmFs3brVGDx4sJGenu5ss2bNGmPYsGFGbm6uZy/gBjJ8+HBj/fr1ynERyMrKMp544glj+/btxoQJ\nE4x58+YZhqHXszt9/vnnxrPPPlvgPuXZfT755BPj1VdfvWwb/T10v7lz5xpPPPGEYRjF/3rWPF4Z\nl5uby4EDB2jatKlzm8lkomnTpvz+++/FGFnpkpiYSFpamkuefX19qVevnjPPe/fupUKFCtx8883O\nNs2aNcNkMrF3716Px3yjyMzMBMDPzw+AAwcOkJeX5/LJS40aNQgMDHTJdXBwMP7+/s42zZs3JzMz\nk6NHj3ow+huDw+EgJiaG8+fPU79+feW4CERGRtKqVat8nxgq1+514sQJHn30UR5//HGmTp3qLCtR\nnt1ny5Yt1KlTh3fffZdHHnmE5557jqioKOd+/T10v9zcXL7//nvnrERxv551z0UZd/r0aRwOh0sN\nHkClSpU4fvx4MUVV+qSlpQEUmOeL+9LS0vLtN5vN+Pn5OduIK8MwmDdvHg0bNqRWrVrAhTx6eXnh\n6+vr0vZKubbZbM59csGRI0d4+eWXycnJwcfHh3HjxlGzZk0OHjyoHLtRTEwMhw8f5u233863T69n\n96lXrx6jRo2iRo0apKWlsWTJEsaPH8/kyZOVZzdKSEhgzZo19OnTh3vvvZd9+/Yxd+5cvL296dix\no/4eFoHY2FgyMzPp3LkzUPz/b2hwIZdkMpmKO4RSzzCMK944ZRiGfheXEBkZybFjx3jttdeu2NYw\njEL1qVz/T82aNZk0aRJnz57lp59+Ytq0aURERFyyvXJ89VJSUpg3bx6vvPIKXl6F/5OsXF+9i/ew\nAAQHB1O3bl1GjRrFjz/+iLe3d4HHKM9XzzAM6tSpw+DBgwEICQnh6NGjrF27lo4dO172OP09vDYb\nNmzglltucQ4OLsVTr2eVRZVxFStWxGw2k56e7rI9PT0934hWrt3Ff/B/zXNGRoYzzzabLd9+h8PB\n2bNn9bsowOzZs/nll1+YMGECdrvdud1ms5Gbm+ssl7ooIyPD+XsoKNeX+jStLLNYLFStWpXQ0FDu\nu+8+ateuzapVq5RjNzpw4AAZGRk899xz3Hfffdx3333Ex8ezatUq7rvvPuW6CPn6+lK9enVOnjyp\nPLtRQEAANWvWdNlWs2ZNZwma/h66V3JyMtu3byc8PNy5rbhfzxpclHFeXl6Ehoayfft25zbDMNix\nYwcNGjQoxshKlypVqmCz2VzynJmZyd69e515rl+/PmfPnuXgwYPONtu3b8cwDOrVq+fxmEuy2bNn\n8/PPPzN+/HgCAwNd9oWGhmKxWNixY4dz2/Hjx0lOTqZ+/frAhVwfOXKEjIwMZ5vffvsNX19fZ3mV\n5GcYBjk5OcqxGzVt2pTJkyczadIk51doaCgdOnRwfq9cF41z586RkJBAQECA8uxGDRo0yFdWffz4\ncef/1fp76F7r16+nUqVK3HLLLc5txf161qNohfLly7N48WICAwPx9vbms88+4/Dhw4wcOVKPor0K\n586d49ixY6SlpbFu3Trq1q2L1WolNzcXX19fHA4Hy5cvp2bNmuTm5jJnzhxyc3N56KGHMJvN+Pv7\ns2/fPmJiYggJCSExMZFZs2bRokULOnXqVNyXV2JERkYSExPD008/jc1m49y5c5w7dw6z2YzFYsHb\n25tTp07x3//+l5CQEM6cOcOsWbMIDAykX79+wIU/brGxsWzfvp3g4GAOHTrE3Llz6d69O82aNSvm\nKywZFi1ahLe3N4ZhkJKSwsqVK/nhhx8YOnQoNWvWVI7dxMvLC39/f5evmJgYqlatSseOHfV6dqOP\nP/7YWf507NgxZs2axenTp3nkkUfw8/NTnt0kMDCQpUuXYjabCQgIYNu2bSxdupTBgwcTHBwMoL+H\nbmIYBh9++CEdO3Z0eQ0W9/8bJqOwBVhSqn377besWLHCuYjeQw89RJ06dYo7rOwsZzkAACAASURB\nVBtKfHx8gfXonTp1YtSoUQB8/vnnREVFcfbsWRo1asTDDz/ssmjQ2bNnmT17tsuiQcOHD9cg708G\nDRpU4PZRo0Y5/+jk5OTw8ccfExMTQ05ODi1atODhhx/Ot3hQZGQkO3fu1GJYBfjPf/7Djh07OHXq\nFL6+vtSuXZu+ffs6nz6iHBediIgIQkJCXBbRU66v35QpU9i9ezenT5/G39+fhg0bct9991GlShVA\neXanrVu3snDhQk6ePEmVKlXo06cPXbt2dWmjv4fX77fffuPNN9/k/fffd8kdFO/rWYMLERERERFx\nCw21RURERETELTS4EBERERERt9DgQkRERERE3EKDCxERERERcQsNLkRERERExC00uBAREREREbfQ\n4EJERERERNxCgwsREREREXELDS5ERERERMQtNLgQERG3GzRoEIcPHy7WGD766CMeeughHn300WKN\nQ0SkLPEq7gBERETcbffu3cTGxjJjxgx8fHyKOxwRkTJDMxciIlKi5eXlXfUxiYmJBAYGlviBxbVc\nm4hISaaZCxGRMmD06NH07NmTn376iWPHjhEaGsrjjz+O3W4nKSmJMWPGMHfuXHx9fQGYN28emZmZ\njBo1yrl/5MiRLFu2jIyMDHr06MEdd9zBtGnT2Lt3L6GhofzrX/+iUqVKznPu3LmT9957j/T0dJo3\nb86jjz5K+fLlAUhISGDevHns3buXcuXKER4ezr333gtAdHQ0q1at4tZbb2XdunU0bNiQp59+Ot81\n/frrryxcuJDExESqVq3KAw88QNOmTVm9ejWffPIJDoeDBx98kDZt2jBq1Kh8x+/fv5958+Zx7Ngx\n7HY79957L+3atXPu/+GHH/jqq69ITEzEz8+PgQMH0qlTp8vumzFjBhUqVODBBx8EIDMzk+HDhzN9\n+nQCAwOZMWMGZrOZrKwsfv31VwYPHkyvXr2IiYlh+fLlJCcnU716dYYNG0b9+vUBiIiIoF69ehw8\neJDff/+d6tWrM3r0aG666SYAsrKyWLhwIVu2bCEzM5MaNWrwzDPPYLfbOXfuHJ9++ilbtmwhJyeH\nFi1aMHz4cHx9fcnNzWXmzJls2bKFvLw8AgMDGTVqFKGhodf9ehORskuDCxGRMuL777/nueeew2az\nMWnSJD777LMC33Rfys6dO5k8eTJJSUk8++yz/P7774wYMYKqVasyceJEvvzyS4YNG+ZyvgkTJmC1\nWnnvvfeYO3cuo0aNIjs7m9dee4077riDcePGcerUKd5++20CAgLo0qULAEePHuW2227jww8/LPDT\n/YSEBCZNmsSTTz5Jq1atiI2N5d///jfvvvsuvXv3pnz58qxevZp33nmnwGvJzMzkrbfeYuDAgXTv\n3p3du3czceJEgoKCqF+/Pj///DNz585l7NixNG7cmIyMDFJTUwEuu68wYmJiGDduHE899RTZ2dls\n3bqVTz75hOeee46QkBBiY2N55513eP/99/Hz83Pm8oUXXqBWrVpERkYyZ84cxo8fD8D06dPJycnh\nrbfewmazcejQIaxWKwAzZszA29ubyZMnY7FY+M9//sOcOXMYM2YM0dHRHD16lGnTplG+fHlOnjzp\nPE5E5FqpLEpEpIzo2bMngYGBeHl50aFDBw4ePHhVx/fv3x+r1UrNmjWpXbs2DRs2pGbNmnh5edG6\ndet8/d19993YbDZ8fX0ZNGgQMTExAGzZsgU/Pz9uv/12zGYzlStXpnfv3vzwww/OY319fbn33nux\nWCwFvuGNiYmhSZMmhIWFYTabue2222jYsKHzHFeydetWKlWqRM+ePTGbzTRu3Jj27dsTHR0NwNq1\na7n99ttp3LgxAP7+/oSEhFxxX2E0b96cZs2aAWC1WlmzZg133XWXs4/WrVtTo0YNfvnlF+cxHTp0\nIDg4GLPZTKdOnThw4AAAaWlpxMXF8eijj2Kz2QAICQnBz8+PjIwMYmNjeeihhyhfvjxWq5UBAwaw\nadMmDMPAy8uLrKwsjh49imEYVKtWDbvdXujrEBEpiGYuRETKiItvPgHKlStHVlbWVR3v7+/vcvyf\nS6CsVivnzp1zaR8YGOjyfW5uLhkZGSQlJXHkyBGGDx/u3G8Yhkv7K73JTU1NJSgoyGVblSpVSElJ\nKdS1pKSkFHj87t27AUhKSnKWQP3V5fYVxp+v82J/ixYt4vPPP3duy8vL49SpU86f//q7u5jr5ORk\nvL29C8xXUlIShmEwZswYl+0Wi4W0tDQ6duxIWloas2bNIjU1lVatWjF06FAqVqx4zdcmIqLBhYhI\nGXfxpufs7GznPRdpaWnXXSKTnJxM3bp1nd97eXnh7+9PYGAgderU4Y033rjksWbz5SfW7XY7e/bs\ncdmWmJhIkyZNChVb5cqVSUpKynf8xTfpQUFBnDx5ssBjL7fPx8eH8+fPO38uqFzKZDLli6V37950\n69atULH/NZacnBxSU1PzDTAqV66M2Wxm5syZeHt7F3h837596du3LxkZGUyZMoWlS5e6DPpERK6W\nyqJERMq4ihUrEhgYSHR0NIZhsGPHDpeSnGu1YsUKTp06xdmzZ/n888+dN0u3bNmS9PR01qxZQ05O\nDg6Hg+PHjxMfH1/ovtu2bUt8fDw///wzDoeDn376id27d7vckH05t9xyizMGh8PBrl27iImJoXPn\nzgB069aNVatWER8fj2EYZGRkcOjQoSvuu/nmm/n1119JS0sjKyuLpUuXXjGWXr16sWLFCmep0/nz\n59m+fXuh7uOoVKkSYWFhzJw5k7S0NAzD4NChQ5w5cwabzUZYWBiRkZGcPn0auDBojI2NBWDHjh0c\nOnQIh8OB1WrF29sbi8VSqPyJiFyKZi5ERMqAv35a/lePPfYYs2bN4ssvv6Rly5a0a9eO3Nzc6zpn\nhw4diIiIcD4t6uLN3j4+Przyyit8/PHHLF26lJycHKpVq8add95Z6L6rVavG2LFjWbhwIdOmTaNq\n1aqMGzcuX6nTpVSoUIEXX3yRefPmsWjRIgICAnjkkUecT2gKCwsjKyuL2bNnk5ycjJ+fH4MGDSIk\nJOSy+zp06EB8fDz/+te/8Pf3Z8CAAfz444+XjaVly5ZkZ2fz0UcfkZiYiLe3N3Xr1uXhhx8u1LWM\nHj2aTz/9lOeff55z585Rs2ZNxo4dC8CoUaP4/PPPeeGFFzhz5gyVKlWibdu2tG7dmvT0dGbPnk1q\naipWq5WmTZvSv3//Qp1TRORSTIZhGMUdhIiIiIiI3PhUFiUiIiIiIm6hwYWIiIiIiLiFBhciIiIi\nIuIWGlyIiIiIiIhbaHAhIiIiIiJuocGFiIiIiIi4hQYXIiIiIiLiFhpciIiIiIiIW2hwISIiIiIi\nbqHBhYjIDWLFihX07NmTypUrU65cOUJDQxk5ciR79+51tjGbzbz77rtuPW96ejoRERHs3r3brf0W\n5ODBg9x5553cdNNNlC9fnpo1azJw4ECXa7yc8+fPExwczOrVq53b1q1bxwMPPEDdunUxm8088cQT\n+Y77/fffGTNmDE2aNKFChQqEhoYyatQoUlJSXNrt37+fkSNHcsstt+Dt7U2zZs3y9XX48GHMZnOB\nX+XLl79s/Bs3buTtt98u1LWWFN27d7/hYhaRoqPBhYjIDeD555+nb9++BAQEEBkZSVRUFOPHj2fX\nrl0MHjy4SM+dlpZGREQE8fHxRXoegDNnzlC9enUmTpzIt99+y7vvvsuePXvo2rUrqampVzx+xowZ\nBAQE0Lt3b+e21atX8+uvv9K5c2cCAgIKPG7t2rXExMTw2GOPsXr1aiIiIli1ahUdO3YkJyfH2W7n\nzp2sXr2aevXq0aRJkwL7ql69Ops3b3b5+vHHH6lUqRJ33HHHZeOPjo6+4d6ov/TSS0yaNIn09PTi\nDkVESgJDRERKtJUrVxomk8mYMGHCJfdfZDKZjMmTJ7v1/AcPHjRMJpPxxRdfuK3P8+fPF7rt3r17\nDZPJZCxatOiKbW+++Wbj/fffv+T+kJAQ4/HHH8+3PTU1Nd+2TZs2GSaTyVi2bFmBfQ0bNsxo2rTp\nFWMyDMPYsGFDoXI4fvx4o2LFioXqszCysrLc1tflhIaGXjbvIlJ2aOZCRKSEmzx5MtWqVePll18u\ncP/tt99+yWNvvvnmfGVAX331FWazmSNHjji3TZw4kXr16lG+fHmqVq1Kjx49OHz4MIcPHyY0NBST\nyUT//v0xm81YLBbnsdnZ2bz44ouEhITg4+ND48aNWbRokcv5hg0bRtOmTVm9ejUtWrTAx8eHb775\nptDXb7fbAVxmEAoSHR3N4cOH6devX6H7vqigGY1bbrkFgOPHj191f3+1cOFCKlWqRJ8+fS7ZJiIi\ngtdee42zZ886y6i6du3q3L97927uvvtubDYbfn5+9OnThwMHDrj0YTabeeedd3j++eepXr06VatW\nBf73O4iKiqJ58+b4+vrSuXNnjhw5wqlTpxg0aBD+/v7UrVuXzz//3KXPmJgYOnXqhM1mw9/fn2bN\nmvHxxx+7tBkwYADz58+/3jSJSCngVdwBiIjIpeXl5bFp0yb69++PxWJxW78mk8n5/YIFC3j11Vd5\n4403uO2220hPT+f7778nIyODhg0bsmzZMu69914mTpxI586dgQulP3DhTeWmTZuYMGECDRs2ZNWq\nVQwZMgS73U7Pnj2d5zp+/DhPPvkkL7/8MsHBwQQHB182PsMwyMvL49ixY7z44ovUrl2bvn37XvaY\nqKgobrrpJmrWrHkdmfmf7777DpPJRKNGja6rn9zcXGcOrVbrJds98sgjHDt2jEWLFrFhwwYMw8Df\n3x+4cC9K27Ztadq0KQsWLMBkMvHGG2/QrVs39uzZg7e3t7OfqVOncttttzFnzhxyc3OBC7+DkydP\n8swzz/DKK6/g5eXFE088wf3330+FChXo2LEjI0aMYObMmQwdOpS///3v3HTTTZw+fZo+ffrQsWNH\nFi9ejNVqJT4+nrS0NJfY27Zty6RJk0hJSaFy5crXlS8RubFpcCEiUoKlpKQ4b1IuKnFxcTRv3pxn\nn33Wue3OO+90fn/xE/y6devSunVr5/YNGzbw9ddfs3btWsLDwwEIDw/n+PHjjB8/3jm4gAv3bXz7\n7bfceuuthYrpH//4B59++qnzvGvXrqVixYpXvI6CbrC+FufPn2fcuHG0bNnSZfbgWqxatYpTp05x\n//33X7ZdjRo1qFWrFmazmbCwMJd9EyZMwG63s27dOudA4u9//zuhoaHMnj2bkSNHOttWrlyZL774\nIl//p06d4vvvv6dhw4YA/PHHHzz++OO88MILvPTSSwDceuutLFu2jOXLl/P444/z+++/k5GRwVtv\nveW8x6RLly75+m7evDmGYRAbG+tyv4uIlD0qixIRKcEMwwBcZxrcrWXLlvzyyy+MHTuWmJgY56fd\nV7J27VoqV65M586dycvLc35169aNX375xRk7XHjDW9iBBcAbb7xBXFwcX3zxBdWrVyc8PJxjx45d\n9pgTJ04QFBRU6HNczqOPPsrhw4dZsGDBdff16aefUrVq1esapKxdu5a7774bs9nszLPNZuOWW24h\nLi7OpW2vXr0K7KNGjRrOgQVA/fr1MZlMzoEhQKVKlahSpQpHjx4FoE6dOlSsWJGRI0eyZMkSkpOT\nC+w7MDAQuPA7EJGyTYMLEZESLDAwEB8fH5f7I9xt2LBhvPfee6xZs4aOHTsSFBTEv/71L86fP3/Z\n45KTk0lJScHb29vl65FHHiE3N9fljebF2v/Cql27Nq1ateKee+7hv//9L3l5efz73/++7DHnzp2j\nXLlyV3Wegrz88sssWrSIpUuXXndJ1NmzZ1m5ciWDBw++rgFicnIyU6ZMccmz1Wrlhx9+cA4ELrpU\nrm02m8vPF0u0Ctp+7tw5575169bh7+/PP/7xD6pVq0aXLl3YsWOHyzEX856VlXXN1ygipYPKokRE\nSjCLxUK7du2IiorC4XBgNl/dZ0I+Pj5kZ2e7bPvrI11NJhOPP/44jz/+OCdOnOCzzz7jueeeIygo\nyFkuUxC73U6VKlVYvXq1yyzFRVWqVHE5x7UqX748jRo1Yt++fZdtZ7fb890LcLU++OADJk6cyLx5\n8+jWrdt19QWwbNkysrKyrlgSdSV2u50+ffowevTofLn+a7mYu2e5br31VlauXMn58+fZsGEDY8eO\n5Z577nFZe+Ri3nW/hYho5kJEpIR7+umnOXnyJG+88UaB+/+8YNxf1apVi127drlsW7NmzSXbV69e\nnaeeeopmzZo5j7v4CffFT7Mv6tatG0lJSXh7e9OyZct8X15e7vn8KiMjg99++406depctl2DBg04\nePDgNZ9n0aJF/Otf/2LixIkMGTLkmvv5a5916tQpdEmY1WotcMaoW7du7NixgxYtWuTLc7169dwS\n65WUK1eOXr168dhjj3Hw4EGXQeuhQ4cwmUw0aNDAI7GISMmlmQsRkRKud+/ejBs3zrmQ3eDBgwkM\nDOTgwYPMmTOHjIyMS95E279/f0aNGsVrr71G27ZtWbVqFZs3b3ZpM3LkSAICArjtttsICAjghx9+\n4LfffmPMmDEAVKtWDZvNxqJFiwgJCaFcuXI0b96cbt260adPH3r27Mmzzz5Ls2bNOHv2LDt37mT/\n/v3MnDnzqq81IiKC9PR02rVrR1BQEAcPHuSDDz4gOzubJ5988rLHtmvXjiVLlpCXl+fyZK0jR44Q\nFxeHYRhkZmayf/9+5w3PFx9bu3HjRoYNG0bXrl3p0KEDP/30k/P4WrVqOZ9AlZWVxapVq4ALK3Fn\nZGQ4++rcubPLJ/dJSUmsW7eOF198sdDX36hRI3Jzc5k6dSpt27bF39+f+vXrExERQevWrenRowcj\nRoygatWqnDx5ko0bN9KxY0cGDRpU6HP8WUEzTn+2atUqZs+ezT333ENwcDAnTpzggw8+oH379i5P\nvvr555/x8/OjRYsW1xSHiJQixbbChoiIXJUVK1YYPXr0MOx2u1GuXDkjNDTUeOyxx4z9+/c725jN\nZuPdd991/pybm2s8++yzRvXq1Y2AgADjscceMz777DPDbDYbhw8fNgzDMObPn2906NDBCAwMNHx9\nfY2//e1vxvTp013OvXz5cqNJkyZG+fLlXY7NyckxXn/9daNBgwaGj4+PUbVqVSM8PNz45JNPnMcO\nGzbMaNasWaGvsUuXLkZQUJBRvnx5o27dusbDDz9sHDx48IrHJiQkGFar1Vi3bp3L9nnz5hkmk8kw\nm835vi6aMGFCgfvNZrMRERHhbHfo0KFL9rVx40aX806fPt0wm83G7t27C3XthnHh9zVmzBijevXq\nhsViMbp06eLct2/fPmPw4MHO3ISGhhrDhg0z4uPjnW3++vu/qKDfQXR0tGE2m40tW7a4bL/55puN\nJ554wjAMw9izZ48xYMAAo3bt2oaPj49Rq1Yt4+GHHzYSEhJcjrnrrruMBx98sNDXKSKll8kwrvCx\nhYiIyA2if//+2Gw2IiMjizuUMuPUqVNUr16dqKgo2rVrV9zhiEgx0+BCRERKjV9//ZX27dtz4MAB\ntz2WVi7v9ddfJzo6mqioqOIORURKAN3QLSIipUbz5s2ZMmVKvsezStGpXLkyH3zwQXGHISIlhGYu\nRERERETELTRzISIiIiIibqHBhYiIiIiIuIUGFyIiIiIi4hZaRE/yOXXqFLm5ucUdRqnm7+9PRkZG\ncYdRJijXnqE8e4by7DnKtWcoz0XPy8uLgIAAz53PY2eSG0Zubi45OTnFHUapZhiGcuwhyrVnKM+e\noTx7jnLtGcpz6aOyKBERERERcQsNLkRERERExC00uBAREREREbfQ4EJERERERNxCgwsREREREXEL\nk2EYxtUcEBERQZMmTejfv39RxXRNoqOjWbJkCdOnTy/uUG54vx9LJCtbT24oSmaLBUdeXnGHUSYo\n156hPHuG8uw5yrVnKM9Xz9fbTAVL4d++e3t7ExQUVIQRuSpVj6I1mUzFHUKp8FrUIfYkninuMERE\nRETkLyL7NaCCpeS+51VZ1P+nReNERERERK7PNc1cnD59mkmTJrFjxw5sNhsDBgygffv2zv1xcXEs\nXbqUxMRE7HY7d9xxB127dgUgPj6eiIgIFi9e7Gz/15KmGTNmkJubi5+fHzExMXh5edGtWzcGDBjg\nPGbbtm188sknJCUlUbduXRo1auQS4+bNm/nyyy9JSEjAarXyt7/9jeHDh1OxYkUAlixZws6dO6lf\nvz4bN24kMDCQoKAgfH19GTFihLOf7du383//93/MnDmTcuXKXUu6RERERETKhGuauVi/fj3du3dn\n7ty5PPjgg3z44Yfs27cPgL179zJlyhQGDBjAnDlz+Oc//8mCBQuIjY29bJ9/LWmKjY2lSZMmREZG\n8vTTT7Ns2TJ2794NQGJiIpMmTaJPnz7MnTuXwYMH8+2337ocX758ecaMGcO8efOYOHEiSUlJzJs3\nz6XNnj178PX1Zfr06YwfP54ePXoQExPD+fPnnW2ioqLo0KGDBhYiIiIiIldwTYOLVq1a0aJFC8xm\nMy1btiQsLIwNGzYAsGHDBsLCwrj11lsxmUw0atSI8PBwoqKiruocjRo1ok2bNphMJho0aEBISIhz\nAPPDDz8QEhJC586dMZvN1KtXj86dO7sc37x5c2666SYA7HY7d955J9u3b3dpY7fb6du3L15eXlit\nVho3bkxgYCA//PADABkZGcTFxdGtW7drSZOIiIiISJlyTWVRVatWdfm5SpUqHDlyBICUlBRq167t\nsr9atWps27btqs4REBDg8rOPjw/nzp0DIDU1tcAY/mzHjh188cUXHDt2jJycHBwOh8uMBFDgnfPd\nu3cnKiqK8PBwoqOjCQkJISQk5KpiFxEREREpCmaLBbvdVuj2nn7g0TUNLhITE/P9bLfbAahcuXK+\n/SdPniQwMBC4MEgAyM7Oxmq1AhcGC1fDbrdz6NAhl20JCQnO73Nzc/n3v//NfffdxwsvvIDVaiU2\nNpbJkye7HFNQsjt27MjChQs5ePAgGzZs4O67776q2EREREREioojL++q3jt7+lG011QWtWXLFrZt\n24bD4eCXX34hLi6OLl26ANClSxfi4uLYunUrDoeD3bt3s379esLDwwGoUaMG5cuXZ+3atRiGwaFD\nh666ZKp9+/YcPHiQ6OhoHA4H+/bt47vvvnPuz83NJScnB19fX6xWKwkJCXz11VeF6tvX15f27dvz\n0UcfkZaWRtu2ba8qNhERERGRsuqaZi66du3K2rVree+997DZbIwcOZJ69eoBUK9ePZ588kkWLVrE\n1KlTCQgIYOjQobRu3Rq4MHMxevRoFixYwOeff07Dhg3p3r0769atK/T5q1Spwrhx4/j444+ZO3cu\ndevWpUePHkRHRzvPMWLECBYvXsycOXMIDg6mQ4cOzns2rqR79+48//zz9OzZ0zm7IiIiIiIil3fV\nK3SXBadPn2bEiBG88847BAcHF3c4HjdkfqwW0RMREREpgSL7NSDIp/D3UdwQZVGlmcPhYNmyZTRq\n1KhMDixERERERK7VNZVFlVaHDh3ilVdeITAwkGeeeaa4wyk2r4aHkJWdU9xhlGpmiwVHXl5xh1Em\nKNeeoTx7hvLsOcq1ZyjPV8/X2wyU3MIjlUVJPklJSeTkaHBRlOx2+1U/JU2ujXLtGcqzZyjPnqNc\ne4byXPRUFiUiIiIiIjckzVxIPr8fS1RZVBHTNLDnKNeeoTx7hvLsOcq1Z5TGPPt6m6lgKTlvrz09\nc6F7LiSf16IO6WlRIiIiItcgsl8DKlg8uyp2SaKyKBERERERcYtiGVw4HI7iOO0llbR4RERERERu\nRG4pi4qIiCA4OJjk5GR27NiBzWZjwIABtG/fHoD4+HgiIiJ48skn+eyzz0hJSWHOnDmYzWaWLFnC\njz/+yNmzZwkODmbYsGGEhIQAsGPHDj799FNOnjyJ2WymZs2aPP/88/j6+rJp0ya++OILUlJS8PLy\nIiQkhJdffhmA0aNHM3DgQDp16uSMcdCgQYwfP57GjRtfczwiIiIiInJpbrvnYv369YwdO5axY8ey\nbds2Jk+eTLVq1ahbt66zzebNm3n77bcpV64cXl5eTJ8+nfT0dF5//XX8/f1Zt24db775Ju+//z6+\nvr5MmzaNwYMH07lzZ/Ly8jhw4ABeXl5kZ2czbdo0Xn75ZRo3bkxubi579uy56pivNh4REREREbk0\nt5VFtWrVihYtWmA2m2nZsiVhYWFs2LDBpc2QIUOoUKECXl5enDlzhu+++45//vOf2Gw2zGYzPXr0\nwM/Pj61btwIX7m5PSEggNTUVi8VCvXr1sFqtAHh5eXHs2DFOnz6Nl5cXTZo0ueqYrzYeERERERG5\nNLfNXFStWtXl5ypVqnDkyJF82y46efIkAM8995xLm9zcXFJSUgB49tln+fLLL3n++ecpX748HTp0\noF+/flitVl588UW++eYbFi9ejN1uJzw8nF69el1VzFcbj4iIiIjI5ZgtFux2W3GH4WQyefbJVW4b\nXCQmJub72W63X7K9zXYh6e+9957z+7+66aabeOKJJwA4fPgwb7zxBoGBgXTu3JmGDRvSsGFD4MI9\nHW+++SbBwcE0btyY8uXLc/78eWc/hVn5sTDxiIiIiIhcjiMvr0StOn7DrtC9ZcsWtm3bhsPh4Jdf\nfiEuLo4uXbpcsn1gYCBhYWHMmjWL5ORkALKysti2bRtpaWnk5uYSHR1NRkYGAOXLl8disWA2m0lL\nS2Pz5s1kZmYC4Ovri9lsxmy+cDmhoaH88MMPZGZmkpmZycKFC68Y/5XiERERERGRy3PbzEXXrl1Z\nu3at85P/kSNHUq9evcse8+STT/LVV1/x+uuvk56ejo+PD/Xq1ePhhx8GLtxw/emnn3L+/HkqVqxI\n586d6dixI2lpaaxdu5ZZs2aRm5uLzWbjvvvuc85kDB48mA8//JDHHnsMmcnLWwAAIABJREFUm83G\nkCFD+P777694DVeKR0RERERELs1kGMZ1r08eERFBkyZN6N+/vztikmI2ZH6sVugWERERuQaR/RoQ\n5FNyVui+YcuiRERERESkbHNbWZSUHq+Gh5CVnVPcYZRqZosFR15ecYdRJijXnqE8e4by7DnKtWeU\nxjz7epuB6y4MumG5pSxKSpekpCRycjS4KEp2u71EPUmiNFOuPUN59gzl2XOUa89QnoueyqJERERE\nROSGVCxlUboBvGQ7dd4gK1sTWkUpJSENR55y7AnKtWcoz56hPHuOcu1+vt5mKliU09JO91xIPq9F\nHdLTokRERMStIvs1oIKl5DxFSYpGmSyLyitlNw6JiIiIiJQEJWLm4qOPPuLXX3/lzJkzBAQE0Lt3\nb3r16gXAwoULOXjwIC+99JKz/cmTJ3nqqaeYOnUqQUFBpKam8sknnxAfH09eXh5NmzZl2LBh+Pv7\nAxfKsIKDgzl16hTbt28nPDycIUOGFMu1ioiIiIiUViVi5qJ+/fr8+9//5v+1d+9hUdb5/8efM8MM\niAjDCKhoanjOEDPRstTyUNm2tmWCnT1kGupWluu3/JmrtWtltmVmqXjMs+7auh1Ms7VLqRW1VfFA\necwDi5wEREAOM78/XGebNMVk7kF4Pa6r64L7+LlfEM77/nzu+7Nw4UIGDx7MRx99REpKCgC9evVi\n9+7dZGZmurf/8ssvadeuHeHh4ZSVlfHqq68SFhbGtGnTmD59OmazmWnTpnmcY+PGjfTq1Yt58+YR\nFxdn6PWJiIiIiNQEVaK4uPPOOwkKCgIgJiaGmJgYd3ERERFBTEwMGzZsAM4Nafr666/p3bs3ANu3\nb6ekpIRHHnkEm82Gv78/jz32GCkpKR6vNouNjaVdu3YA2Gw2Iy9PRERERKRGqBLDolatWkVSUhKn\nTp3CZDJRUlJCnTp13Ot79+7NrFmziIuLY+vWrVgsFjp06ACcGyKVk5PDoEGDPI5ps9nIysrC4XAA\n54oUEREREfENs8WCw2H3WGa1Wt2f1cQ7TCZjH6L3eXGxefNmvvjiC8aPH0/jxo0BePPNN/np3H4d\nOnTAz8+Pbdu2sWHDBnr06IHZfK7TxW63U69ePd55551Lnuf89iIiIiJiPGd5+QUT5mkSPe+rcZPo\nFRYW4ufnR1BQEE6nk+TkZPeQqPNMJhO9evXir3/9K3v27KFHjx7udZ07d6a0tJSVK1dSWFgIQF5e\nHt98842h1yEiIiIiUtP5vOfijjvuIDU1ldGjR2O1WomNjSU2NvaC7e68805WrlxJTEwMYWFh7uUB\nAQG89tprLFmyhBdffJHCwkJCQkKIiYmhS5cuRl6KiIiIiEiNZnL9dPxRFVZeXs6wYcNISEhwP28h\n3vHYgmRNoiciIiKVKrFfK8IDPMf/a1iU99W4YVEVtXbtWmrXrq3CQkRERESkivL5sKjLKSgoICEh\ngTp16jBq1ChfN6dGeKVnU4pKSn3djGrNbLHg1EzxhlDWxlDOxlDOxlHWlS/QagauiQEzchWumWFR\nYpzMzExKS1VceJO6gY2jrI2hnI2hnI2jrI2hnL1Pw6JEREREROSaVOWHRYnxTp11UVSiDi1vyj6Z\ni7NcGRtBWRtDORujOuUcaDVT21I9rkVE/qdaFBcbN25k5cqVvP/++75uSrUwacMRvS1KRES8KrFf\nK2pbjJ05WES8r9oMizJ6anMREREREfFUbYoLERERERHxLa8Mi5o4cSJNmjQhOzubXbt2ERwczNCh\nQ7FYLMybN4+srCzatm3LqFGjCAgIAGD58uUkJSWRm5tLnTp16NatG/Hx8e5jlpSUsGrVKrZs2UJu\nbi52u51HH32UTp06ubdZv349H3/8MYWFhcTExDB8+HD38UVERERExLu89szFpk2beOmllxg9ejTL\nli1j+vTptGnThkmTJuF0Ohk/fjyffvop/fr1A6Bhw4ZMnDiR0NBQDh06xJ/+9CfCw8Pp0aMHADNm\nzCArK4uXXnqJ+vXrk5OTQ0HB/54LyM7O5uTJk7z77rsUFBQwfvx4PvvsMx588EFvXaKIiIiIiPyE\n14ZF3XLLLTRv3hyTyUTXrl3Jy8vjt7/9LYGBgQQFBXHTTTdx8OBB9/a33347oaGhAERFRdG1a1d2\n7doFQH5+Pt9++y1PP/009evXB869F7lx48bu/f38/HjkkUfw8/PDbrfTqVMnDhw44K3LExERERGR\nn/Faz8X5QgHA398fALvd7l5ms9koKipyf79u3Tq+/PJLMjMzASgtLaVly5YA7mUNGjT4xfOFhIRg\nNv+vVgoICPA4voiIiFQdZosFh8N++Q19xGq14nA4fN2Mak85e5/RLz2qEq+i/f7771mwYAHjx4+n\nVatWmEwm5s+fz48//gjgnlXwP//5j0dvhYiIiFybnOXlVXpmZs0cbQzl7H01cobuoqIizGYzwcHB\nmEwm9u3bx6ZNm9zrg4ODue2220hMTCQ9PR2AnJwcjh496qsmi4iIiIjIz1SJnouYmBh69OjB//t/\n/w+A6Ohounbt6u65ABg+fDgrV67kT3/6E3l5eYSGhvLoo4+qJ0NEREREpIowuVwul68bIVXLYwuS\nNUO3iIh4VWK/VoQHVN0JcDVcxxjK2ftq5LAoERERERG59lWJYVFStbzSsylFJaW+bka1ZrZYcJaX\n+7oZNYKyNoZyNkZ1yjnQagY0eEKkulFxIRcI9TcRZK66XdXVgcNhVzewQZS1MZSzMapXziosRKoj\nDYsSEREREZFKYXjPxcqVK9m7dy8TJkww+tRSQafOuigq0R0lb8o+mYuzXBkbQVkbQzkbw6icA61m\nalv08xSRK+fV4mLixIm0bduWhx56yJunkUo2acMRvS1KRKQGS+zXitoWDY8VkStXI4ZFlZWV+boJ\nIiIiIiLVntd6LmbPns2+ffv44YcfWLNmDbVq1WLmzJnu9atWrWL9+vWUlZVx6623MmTIEEymc3dJ\ncnJyWLRoEXv37qW8vJzo6GgGDhxIcHAwAAUFBSxcuJCdO3fidDpp06YNAwcOxOFwADBjxgxKS0sJ\nCAhg69attG3blqysLDp27MgDDzzgbsNXX33F6tWree+997wVg4iIiIhIjeG1nouhQ4fSpk0bHnjg\nARYuXOhRWKSmplK7dm0++OADXn31VZKSkti8eTNwrpfh1VdfJSwsjGnTpjF9+nTMZjPTpk1z7//e\ne++Rm5vL1KlTee+997DZbLzxxhv8dD7ALVu2cMMNNzBr1ixGjBjBXXfdxVdffeXRxg0bNtC7d29v\nRSAiIiIiUqP4ZFhUvXr16NOnD2azmcjISKKjozlw4AAA27dvp6SkhEceeQSbzYa/vz+PPfYYKSkp\n5OTkkJuby44dOxg4cCBBQUEEBAQwePBgjh49ysGDB93naNGiBV27dsVsNmOz2ejSpQuFhYXs2rUL\ngB9//JEjR45wxx13+CICEREREZFqxyfzXISGhnp8HxAQQFFREQDp6enk5OQwaNAgj21sNhtZWVmY\nzefqoYiICPe6wMBA6tSpQ1ZWFs2bN79gPZyb+rx79+5s2LCBdu3a8eWXXxIbG+seaiUiIiLnmC0W\nHA67r5vhU1ar1T3cWrxHOXvf+ccOjOLV4uLXXIzdbqdevXq88847F12fm5sLQEZGBpGRkQAUFhZy\n+vRpwsLCLnnuu+66ixdeeIHMzEw2b97Miy++eMXtExERqe6c5eXVaLK+X8fhcNT4DIygnL3ParUS\nHh5u2Pm8OizKbreTlpZ2Rft07tyZ0tJSVq5cSWFhIQB5eXl888037mO2b9+eBQsWcPr0aYqLi5k7\ndy6NGzemWbNmlzx2/fr1adOmDVOnTiU4OJi2bdv+ugsTEREREZELeLW4uO+++zh27BiDBg3imWee\nqdA+AQEBvPbaa2RkZPDiiy8ycOBAXnnlFVJTU93bjBo1ipCQEF588UVGjRrF2bNn+cMf/lChnpLe\nvXtz+PBhPcgtIiIiIlLJTK6fvmKpBjhy5Ajjxo3jww8/pE6dOr5uTpX02IJkTaInIlKDJfZrRXhA\nzZ5ET8N1jKGcva9aDYuqakpLS1m9ejVdu3ZVYSEiIiIiUsl88rYoX9i2bRvvvvsujRs35g9/+IOv\nm1OlvdKzKUUlpb5uRrVmtlhwlpf7uhk1grI2hnI2hlE5B1rNQI0a2CAilaTGDYuSy8vMzKS0VMWF\nN6kb2DjK2hjK2RjK2TjK2hjK2fs0LEpERERERK5JKi5ERERERKRS+PSZixEjRhAXF0f37t2vyeNX\nV6fOuigq0Wg5b8o+mYuzXBkbQVkbQzl7V6DVTG2L8hWRqq/GPNAtFTdpwxG9ilZEpApJ7NeK2paa\n/WpYEbk2aFiUiIiIiIhUCq/3XKxdu5ZPP/2U/Px8/P39ad++PQkJCe712dnZTJ48mdTUVOx2O48/\n/jgdO3Z0r//yyy/59NNPOXXqFPXq1SMuLo6bb77ZvT41NZXly5dz9OhRAKKiohg3btwF7SgrK2Pm\nzJmkp6czZswYgoODvXjVIiIiIiI1j1eLi/T0dBYvXszkyZNp1KgRZ8+e5fDhwx7bfPXVV4wZM4Ym\nTZqwZs0apk+fzsyZM/H39+ebb75hyZIljB07lhYtWrBt2zbefvttXn31VaKiojh69CivvvoqgwcP\nplu3bpjNZvbu3XtBOwoKCpgyZQoOh4MJEybg56fRYCIiIiIilc2rw6LM5nOHP3bsGEVFRfj7+9O6\ndWuPbXr16kWTJk0AuOuuuygqKiItLQ2Af/7zn/Ts2ZNWrVphNpvp1KkTN998M1999RUA69ev56ab\nbqJnz55YrVYsFgvR0dEexz9x4gTjxo2jTZs2PPvssyosRERERES8xKuftCMiInj22WdZt24ds2bN\nIjIykvvuu49bb73VvU1oaKj764CAAACKioqAc0OmOnfu7HHM+vXru4dAZWZm0rhx40u24euvv8bf\n35++fftWyjWJiIgYzWyx4HDYsVqtOBwOXzenRlDWxlDO3mcyGfsyCK/fxu/YsSMdO3bE6XSyZcsW\n3nnnHZo1a0ZERMRl961bty4ZGRkey9LT0wkLCwMgPDzc3cvxSwYMGMD333/PhAkTGDduHHa7/ddf\njIiIiA84y8vJycnRbMYGUtbGUM7eV61m6E5LS2PHjh0UFxdjNpupVasWJpPJPVzqcu688042bNjA\n999/j9PpZOvWrWzfvp0ePXoAcPfdd7Nz506++uorSktLKSsrIyUlxeMYZrOZ4cOHEx0dzYQJEy4o\nVkREREREpHJ4teeirKyMv/71rxw/fhyXy0VYWBijRo1y9zxcrpumS5cuFBYW8uGHH7rfFvX8888T\nFRUFQKNGjRg3bhxLly5l0aJFmEwmmjVr5n7u4qfHf+KJJwgKCnL3YDRq1MhLVy0iIiIiUjOZXC6X\npvwUD48tSNYkeiIiVUhiv1aEB5g0hMRAytoYytn7qtWwKBERERERqTn0Xla5wCs9m1JUUurrZlRr\nZosFZ3m5r5tRIyhrYyhn7wq0mgENNBCRqk/FhVwg1N9EkNnY15bVNA6HXd3ABlHWxlDO3qbCQkSu\nDRoWJSIiIiIilUI9F3KBU2ddFJXoLpk3ZZ/MxVmujI2grI2hnC8t0GqmtkX5iEj1Z3hxMXHiRNq2\nbctDDz1k9KmlgiZtOKK3RYmIVKLEfq2obdFwUxGp/qrlsKgRI0bw9ddf+7oZIiIiIiI1SrUsLkRE\nRERExHg+eeaisLCQadOmsX37dmrXrs2DDz5Ir1693Ov379/PkiVLOHr0KAEBAXTr1o3+/ftjNp+r\nhWbOnMnOnTspKCggNDSUPn36cM899wAwefJksrKymD17NnPnzqVRo0b86U9/8sVlioiIiIjUKD4p\nLjZu3MiYMWP4/e9/z7fffsu0adOIiYkhPDyctLQ0XnvtNRISEujUqRPZ2dlMmTIFm83GAw88AEDL\nli159NFHCQoKYufOnbz55ps0bNiQ6OhoXnrpJUaMGEF8fDzdunXzxeWJiIiIiNRIPikubrnlFtq0\naQPArbfeSmJiIocPHyY8PJwvvviCTp060blzZwDCwsK4//77WbZsmbu4uPPOO93HiomJISYmhpSU\nFKKjo93LXS69lUNERKoGs8WCw2G/6uNYrVYcDkcltEguR1kbQzl7n8lk7MskfFJc/PyXKCAggKKi\nIgDS09PZs2cP27Ztc693uVwexcKqVatISkri1KlTmEwmSkpKqFOnjjGNFxERuULO8vJKmWTQ4XBo\nskKDKGtjKGfvs1qthIeHG3a+KjfPRUhICN26dePpp5++6PrNmzfzxRdfMH78eBo3bgzAm2++6VF8\nnH82Q0REREREjFPlPoXffffdfPvtt2zZsoWysjKcTifp6ens2LEDOPcwuJ+fH0FBQTidTpKTk0lJ\nSfE4ht1uJy0tzRfNFxERERGpsapEz8VPx4I1a9aMcePGsXz5cmbPnk15eTkRERH07t0bgDvuuIPU\n1FRGjx6N1WolNjaW2NhYj+P169ePefPmsX79eho2bMirr75q6PWIiIiIiNREJpeefJafeWxBsmbo\nFhGpRIn9WhEecPUPVWp8unGUtTGUs/cZ/cxFlRsWJSIiIiIi16YqMSxKqpZXejalqKTU182o1swW\nC87ycl83o0ZQ1sZQzpcWaDUDGiggItWfigu5QKi/iSCzse9ErmkcDru6gQ2irI2hnC9HhYWI1Awa\nFiUiIiIiIpXimui52LhxIytXruT999+v1OPGx8czYcIEbrjhhko97rXu1FkXRSW6y+ZN2SdzcZYr\nYyMoa2NU55wDrWZqW6rntYmIVLYqV1zMmDEDgISEBI/lRk9dXpNN2nBEb4sSEfmvxH6tqG3Rv0Ei\nIhWhYVEiIiIiIlIprqrnYuLEiTRp0oTs7Gx27dpFcHAwQ4cOxWKxMG/ePLKysmjbti2jRo0iICAA\nODfD9uLFi9mxYwfFxcW0aNGCwYMHExERwerVq9m0aRMmk4l//etfmEwmj6FQ69ev5+OPP6awsJCY\nmBiGDx/uPm52djbz588nNTUVi8VC+/btefzxx6lduzYA+fn5zJo1iz179hAUFMSAAQOu5tJFRERE\nRORnrrrnYtOmTdx///3Mnz+fLl26MH36dNatW8ekSZOYPn06aWlpfPrpp+7tp0yZQklJCVOmTGHm\nzJk0btyY119/HafTyQMPPEDXrl25/fbbWbhwIQsWLCAoKAg4VzycPHmSd999l7/85S8cPHiQzz77\nDACn08nkyZMJDAxk+vTpTJkyhaysLI/CZNq0aZSVlfH+++/zxhtvkJSUdLWXLiIiIiIiP3HVxcUt\nt9xC8+bNMZlMdO3alby8PH77298SGBhIUFAQN910EwcPHgTg0KFD7N+/n6FDhxIYGIifnx8DBgwg\nKyuL/fv3X/I8fn5+PPLII/j5+WG32+nUqRMHDhwA4MCBA5w4cYJBgwbh7+9PnTp1ePLJJ9m+fTt5\neXnk5OSQkpLCE088QWBgIIGBgTz66KNXe+kiIiIiIvITV/1Ad2hoqPtrf39/AOx2u3uZzWajqKgI\ngPT0dEpLSxk2bJjHMVwuF9nZ2Zc8T0hICGbz/2qhgIAA93Gzs7MJDg52D5ECqF+/PgBZWVm4XOfe\n8hEREeFe/9OvRUREfonZYsHhsF9+QwNYrVYcDoevm1EjKGtjKGfvM/qlSIa+Lcput2Oz2ZgzZ45H\nofBTJpPJXQxUVN26dcnPz6e4uNhdYKSnpwMQFhZG+X9njc3IyCAyMhKAkydP/trLEBGRGsRZXl5l\nJgh0OBxVpi3VnbI2hnL2PqvVSnh4uGHnM/RtUa1bt6ZRo0YkJiaSn58PQEFBAVu2bKGkpAQ4V4Cc\nPHkSp9NZ4eM2b96cRo0aMX/+fIqLi8nPz2fhwoXcfPPNhISE4HA4iI6OZtGiRZw5c4aCggKWLVvm\nlWsUEREREampDC0uzGYz48ePx2q18vLLL/Pkk08yduxYtm7d6u6y6dWrF06nkyFDhjBo0CDOnDlT\noeOOHTuWgoICRo4cyZgxY6hbty4jRoxwbzNq1CjMZjMjRozgpZdeokuXLl67ThERERGRmsjkutIx\nSFLtPbYgWZPoiYj8V2K/VoQHVI1J9DSExDjK2hjK2fuq9bAoERERERGpvgx9oFuuDa/0bEpRSamv\nm1GtmS0WnP990YB4l7I2RnXOOdBqBtTJLyJSESou5AKh/iaCzFVjCEB15XDY1Q1sEGVtjOqdswoL\nEZGK0rAoERERERGpFOq5kAucOuuiqER36rwp+2QuznJlbARlbYyrzTnQaqa2RT8nEZFrXZUtLl54\n4QUeeOABbr/9dl83pcaZtOGI3hYlIoZK7NeK2hYNxxQRudZV2eJi6tSpvm6CiIiIiIhcAT1zISIi\nIiIilcKw4mLbtm0kJCS4v1+7di3x8fHs2bMHgMLCQh5++GFOnjwJwIgRI/j6668ByMzMJD4+nk2b\nNjFmzBiefPJJxo8fT1pamvt4xcXFzJgxgyFDhvDMM8/wySefeBxDRERERES8y7Di4sYbbyQ3N5f/\n/Oc/AKSkpNCgQQN27doFwO7duwkLC6NevXq/eIxNmzYxfvx45syZQ0hICHPmzHGvmz9/PidOnGDq\n1Km8++67pKWlcerUKe9elIiIiIiIuBlWXAQEBNCiRQt27tyJ0+lk7969DBgwgJ07dwKwa9cuoqOj\nL3mM/v37ExwcjJ+fHz169ODAgQMAuFwuNm3aRHx8PHa7HZvNxhNPPIHLpTePiIiIiIgYxdAHuqOj\no9m1axfXX389ERERxMbGMnPmTE6fPk1KSgoPP/zwJfcPDQ11fx0QEEBxcTEA+fn5lJWVER4e7rG+\nTp063rkQERGpVGaLBYfD7utmVHlWqxWHw+HrZtQIytoYytn7TCZj38RnaHHRrl07/vGPf3DdddfR\nrl07LBYLbdq0YcOGDWRkZHDjjTf+quOe783IzMykQYMGwLlnME6fPl2ZzRcRES9xlpdX4xm+K4/D\n4VBOBlHWxlDO3me1Wj1uwHuboW+Lat68OWazmXXr1hETEwOcKzj+/ve/c/311xMUFPSrjmsymeja\ntSsrVqwgNzeXs2fP8tFHHxleqYmIiIiI1GSGFhdms5m2bdtSXl5O69atgXPFRWFhIe3atfPY9koL\ng4EDBxIZGcno0aN57rnniIyMJDg4GKvVWmntFxERERGRX2ZyVdOnngsLCxk8eDCvvvoqLVq08HVz\nrimPLUjWDN0iYqjEfq0ID1Bv8+VoCIlxlLUxlLP3VethUd6UmZlJamoqTqeTgoICEhMTqV+/Ps2a\nNfN100REREREagRDH+j2ptLSUhITE8nMzMTPz4/mzZvzf//3f5jN1aZ+MswrPZtSVFLq62ZUa2aL\nBWd5ua+bUSMoa2Ncbc6BVjNQLTvSRURqlGpTXERGRvLWW2/5uhnVQqi/iSCzhid4k8NhVzewQZS1\nMa4+ZxUWIiLVgW7ri4iIiIhIpag2PRfeMnv2bEwmE0899ZSvm2KYU2ddFJXoLqI3ZZ/MxVmujI2g\nrI3xa3IOtJqpbdHPRkSkOlFxcRlDhw71dRMMN2nDEb0tSkS8LrFfK2pbNARTRKQ6uaaHRZWVlfm6\nCSIiIiIi8l9X1HOxdu1aPv30U/Lz8/H396d9+/YkJCQAEB8fz4QJE7jhhhuAc6+GHTlyJO+//z5h\nYWFs3LiRlStX0qdPHz755BNKS0uJjY1l8ODB2Gw24NzcFIsXL2bHjh0UFxfTokULBg8eTEREBAAz\nZsygtLSUgIAAkpOTufHGGxk2bBizZs0iJSWFsrIyQkNDefjhh+ncuTMAW7duZdWqVWRkZOBwOPjN\nb35Djx49PNo4cuRI1qxZQ0ZGBo0bN+aZZ54hMjLSfU7AfZ0FBQUsWbKEnTt3UlBQQHh4OEOHDqVV\nq1ZX9YMQEREREbnWVbi4SE9PZ/HixUyePJlGjRpx9uxZDh8+fEUny8nJ4cSJE0ybNo0zZ87w5ptv\nsnDhQvfzDFOmTCEsLIwpU6Zgs9lYsWIFr7/+Om+99Zb7lbJbtmzhmWeeYejQoZSVlfG3v/2N4uJi\nZsyYgb+/P1lZWZw9exaA/fv388477/D8889z8803k5qayhtvvEFQUBCdOnVyt2vTpk2MHz+ewMBA\n3nnnHebMmcP48eMvaL/L5eKNN96gTp06vPbaa4SGhpKenn7Fs4mLiIiIiFRHFR4Wdf7D/bFjxygq\nKsLf35/WrVtf8QkHDhyIzWYjNDSU+Ph4vv76awAOHTrE/v37GTp0KIGBgfj5+TFgwACysrLYv3+/\ne/8WLVrQtWtXzGYzNpsNPz8/CgoKOH78OC6Xi7CwMBo2bAjAP//5T2JjY+nYsSMmk4k2bdrQs2dP\nNmzY4NGm/v37ExwcjJ+fHz169ODAgQMXbfvBgwc5cOAAI0eOJDQ0FID69etTr169K85BRERERKS6\nqXDPRUREBM8++yzr1q1j1qxZREZGct9993HrrbdW+GTBwcH4+/t7HLOkpIT8/HzS09MpLS1l2LBh\nHvu4XC6ys7M99vmpvn374nQ6+fDDD8nJySE6OppHHnmEiIgIsrOzadKkicf29evXZ8eOHR7LzhcK\nAAEBARQXF1+0/VlZWdSpU4fAwMAKX7OIiFyc2WLB4bD7uhnXFKvVisPh8HUzagRlbQzl7H1Gj7C5\nomcuOnbsSMeOHXE6nWzZsoV33nmHZs2aERERQUBAgHs4EnDRyZROnz7N2bNn3QXGyZMnsVqtBAcH\nY7fbsdlszJkz55Kzav88IJvNRlxcHHFxcZw5c4bExEQ++OADJkyYQN26dcnIyPDYPj09nbCwsCu5\nbLfw8HBOnz5NYWGhCgwRkavkLC/XBIdXyOFwKDODKGtjKGfvs1qthIeHG3a+Cg+LSktLcz9obTab\nqVWrFiaTyV0IREVF8c9//pPS0lJyc3NZtWrVBcdwuVwsXLiQkpLxt4kBAAAW2klEQVQScnJyWLVq\nFXfccQcArVu3plGjRiQmJpKfnw+ce3h6y5YtlJSU/GK7tm3bxvHjx3E6nVitVmw2m7tNd955J1u3\nbuW7777D6XSSmprKV199Rc+ePSsc0E81a9aMli1bMmPGDE6dOgWcK1bS09N/1fFERERERKqTCvdc\nlJWV8de//tXj2YZRo0a5ewGGDBnCzJkzeeqpp4iIiOD+++9n165dHseoW7cukZGR/P73v3e/Lerx\nxx8Hzj3TMX78eJYvX87LL7/M6dOnCQoKok2bNnTo0OEX25WRkcFHH31Ebm4ufn5+tGjRwj20qkWL\nFjz77LMsXbqUadOmERoayuOPP+7xMPeVGjNmDEuWLOHll1+msLCQ8PBwnn76aerXr/+rjykiIiIi\nUh2YXC6XIdOjbty4kVWrVjF9+nQjTidX4bEFyZpET0S8LrFfK8ID9La9K6EhJMZR1sZQzt5XZYdF\niYiIiIiIXMoVPdAtNcMrPZtSVFLq62ZUa2aLBWd5ua+bUSMoa2P8mpwDrWbAkM5zERExiGHFxR13\n3OF+eFuqtlB/E0FmDVXwJofDrm5ggyhrY/y6nFVYiIhUNxoWJSIiIiIilULFhYiIiIiIVAoVFyIi\nIiIiUilUXIiIiIiISKVQcSEiIiIiIpVCr6KVC/j56dfC20wmE1ar1dfNqBGUtTGUszGUs3GUtTGU\ns/cZ/bnOsBm6RURERESketOwKPGwZs0aXzehRpg/f76vm1BjKGtjKGdjKGfjKGtjKGdjGPn5TsWF\neNi3b5+vm1AjnDx50tdNqDGUtTGUszGUs3GUtTGUszGM/Hyn4kJERERERCqFigsREREREakUKi5E\nRERERKRSWP74xz/+0deNkKqlcePGvm5CjaCcjaOsjaGcjaGcjaOsjaGcjWFUznoVrYiIiIiIVAoN\nixIRERERkUqh4kJERERERCqFigsREREREakUKi5ERERERKRSqLgQEREREZFK4efrBkjVsHbtWv7x\nj3+Qm5tL06ZNGTRoEM2bN/d1s64Zq1evJjk5mbS0NGw2Gy1btuTRRx8lMjLSvU1paSkLFizg22+/\npbS0lJiYGJ566ilCQkLc22RlZTF79mz27t1LQEAA3bt355FHHsFs1n2Ai1m9ejXLli3j3nvv5ckn\nnwSUc2XKyclh8eLF7Nixg7Nnz9KgQQOeeeYZoqKi3NssX76cr776ijNnztCqVSuGDh1K/fr13esL\nCgqYO3cu27dvx2w207lzZwYOHEhAQIAvLqnKcTqdrFixgs2bN5Obm0toaCh33HEH/fr189hOOV+5\nffv2sWbNGg4dOkRubi5jxoyhY8eOHttURq4//vgjc+fO5cCBA4SEhHDPPffQt29fw67T1y6Vc3l5\nOUuXLmXHjh2cPHmSwMBAoqOjefTRRwkNDXUfQzlfXkV+n8+bNWsWGzZs4Mknn+Tee+91LzcqZ81z\nIXzzzTckJibyxBNPEB8fT0ZGBkuWLKFHjx74+/v7unnXhI8//pgePXrw0EMP0a1bN3bt2sUnn3xC\n7969sVgsAMydO5cdO3bw7LPP0rt3b7755hv+9a9/ceeddwLnPmS88sorBAQE8PzzzxMdHc2KFSso\nKirixhtv9OXlVUkHDhxg6dKlhIeHExERQfv27QHlXFnOnDnDyy+/TIMGDRg0aBB9+/YlKioKh8NB\n7dq1gXO/959++inDhw+nb9++pKam8sknn3DXXXe5C7W33nqLzMxMRo8eTZcuXfj88885fPgwnTt3\n9uXlVRmrV6/miy++YPjw4cTFxXHdddexaNEiatWq5b7Bo5x/nRMnTlBeXk6PHj349ttvue222zxu\n+FRGrkVFRbz88stERUUxatQomjRpwoIFCwgJCfEowquzS+VcXFzM2rVrue++++jfvz+xsbFs2rSJ\nzZs306tXL/cxlPPlXe73+bzk5GQ2b96MxWKhVatWtGjRwr3OsJxdUuO9/PLLrrlz57q/dzqdrmHD\nhrk+/vhjH7bq2paXl+eKi4tz7du3z+VyuVxnzpxxPfzww64tW7a4tzlx4oQrLi7OtX//fpfL5XJ9\n9913rgEDBrjy8vLc26xbt841cOBAV1lZmbEXUMUVFRW5fv/737tSUlJcf/zjH13z5893uVzKuTIt\nWrTI9corr1xym6efftr1j3/8w/39mTNnXI888ogrKSnJ5XK5XMeOHXPFxcW5Dh065N7m3//+tys+\nPt516tQp7zT8GjN58mTXBx984LHsrbfecr333nvu75Xz1YuLi3Nt3brVY1ll5PrFF1+4Bg8e7PG3\nY/Hixa7nnnvOm5dTZV0s5587cOCAKy4uzpWVleVyuZTzr/FLOWdnZ7uGDx/uOnbsmCshIcH16aef\nutcdP37csJw1BqCGKysr49ChQ0RHR7uXmUwmoqOj+eGHH3zYsmtbYWEhAEFBQQAcOnSI8vJyjzvj\nkZGRhIWFuXPev38/jRs3Jjg42L1NTEwMhYWFHDt2zMDWV32JiYncfPPNF/Q0KOfKs337dpo1a8bb\nb7/N0KFDGTt2LBs2bHCvz8jIIDc31+NvR2BgIC1atPDIunbt2lx//fXubdq1a4fJZGL//v3GXUwV\n1qpVK3bv3s1//vMfAI4cOcL333/PTTfdBChnb6msXH/44QfatGnj7qGGc39P0tLS3P8OiKczZ85g\nMpncPaDKuXK4XC6mT5/O/fffT6NGjS5Y/8MPPxiWs565qOFOnz6N0+n0GI8OEBISQlpamo9adW1z\nuVzMnz+f1q1bu/8Hz83Nxc/Pj8DAQI9tQ0JCyM3NdW/z85+D3W53r5NzkpKS+PHHH5k8efIF65Rz\n5Tl58iTr1q3jvvvu48EHH+TAgQPMmzcPq9VKt27d3Fld7G/HpbI2m80EBQUp6//63e9+R1FREc89\n9xxmsxmXy8WAAQO47bbbAJSzl1RWrnl5eURERFxwjPP7//xvUU1XWlrKkiVLuP32293j/JVz5fj4\n44/x8/Pjnnvuueh6I3NWcSG/yGQy+boJ16TExESOHz/OpEmTLruty+Wq0DH1szgnOzub+fPnM378\nePz8Kv7nSzlfOZfLRbNmzRgwYAAATZs25dixY6xfv55u3bpdcr/LPRjvcrmU9X998803bN68meee\ne45GjRpx5MgR5s+fj8PhUM4+oFy9p7y8nLfffhuTycRTTz112e2Vc8UdOnSIzz//nDfffPOK9/VG\nziouarg6depgNpvJy8vzWJ6Xl3dBhSuXN2fOHP79738zadIkHA6He7ndbqesrIzCwkKPyj8/P999\n19xut3Pw4EGP4/3S3bWa6tChQ+Tn5zN27Fj3MqfTyd69e1m7di3jxo1TzpUkNDSUhg0beixr2LAh\nycnJwP96e/Ly8txfw7msmzZt6t7m539bnE4nZ86cUdb/tWjRIh544AFuvfVWAK677joyMzNZvXo1\n3bp1U85ecrW5nt8nJCTkov9+/vQc8r/CIjs72/1CjfOU89VLTU0lPz+fZ555xr3M6XSycOFCPvvs\nM6ZPn25oznrmoobz8/MjKiqKlJQU9zKXy8Xu3btp1aqVD1t27ZkzZw7btm1jwoQJhIWFeayLiorC\nYrGwe/du97K0tDSysrJo2bIlAC1btuTo0aPk5+e7t9m1axeBgYEXHT9ZE0VHRzN16lSmTJni/i8q\nKoquXbu6v1bOlaNVq1YXDI1MS0tz/25HRERgt9s9/nYUFhayf/9+99+Oli1bcubMGQ4fPuzeJiUl\nBZfL5fEGk5qspKTkgruGJpPJ3dumnL3janM9/yavli1bsm/fPpxOp3ubnTt3EhkZqaE6/3W+sMjI\nyOCVV15xP4t4nnK+et26deOtt97y+LcxNDSUvn37Mm7cOMDYnPUqWqFWrVosX76csLAwrFYry5Yt\n48cff2T48OF6FW0FJSYmkpSUxOjRo7Hb7RQXF1NcXIzZbMZisWC1Wjl16hRr166ladOmFBQUMHv2\nbMLCwtzvs4+IiCA5OZmUlBQaN27MkSNHmDdvHr1796Zdu3Y+vsKqwc/Pj+DgYI//kpKSqFevHt26\ndVPOlSgsLIxVq1ZhNpsJDQ1lx44drFq1igEDBtC4cWPg3F2vjz/+mIYNG1JWVsbcuXMpKytj8ODB\nmM1mgoODOXDgAElJSTRt2pSMjAxmz55N+/bt6d69u4+vsGo4ceIEX3/9NZGRkfj5+bFnzx6WLVvG\n7bff7n7YWDn/OsXFxRw/fpzc3Fy+/PJLmjdvjs1mo6ysjMDAwErJtUGDBqxfv56jR48SGRnJ7t27\nWbp0KfHx8R4PzlZnl8o5ICCAqVOncuTIEV544QWsVqv730c/Pz/lfAUulbPdbr/g38bPP/+cdu3a\n0aFDBwBDcza5KjoYWaq1L774gjVr1rgn0Rs8eDDNmjXzdbOuGfHx8RddnpCQ4P6ftrS0lI8++oik\npCRKS0tp3749Q4YMuWByt8TERPbs2aPJ3Spo4sSJNG3a1GMSPeVcOb777juWLFlCeno6ERER3Hff\nffTo0cNjmxUrVrBhwwbOnDlDmzZtGDJkiMckZGfOnGHOnDkekzYNGjRINy7+q7i4mOXLl5OcnEx+\nfj6hoaHcfvvt9OvXz+ONLcr5yu3du5eJEydesLx79+4kJCQAlZPr0aNHmTNnDgcPHqROnTr06dOn\nRk3udqmc+/fvz8iRIy+634QJE7jhhhsA5VwRFfl9/qmRI0dy7733ekyiZ1TOKi5ERERERKRS6Dad\niIiIiIhUChUXIiIiIiJSKVRciIiIiIhIpVBxISIiIiIilULFhYiIiIiIVAoVFyIiIiIiUilUXIiI\niIiISKVQcSEiIiIiIpVCxYWIiIiIiFQKFRciIlLp4uPj+fHHH33ahpkzZzJ48GCGDRvm03aIiNQk\nfr5ugIiISGVLTU0lOTmZGTNmEBAQ4OvmiIjUGOq5EBGRKq28vPyK98nIyCAsLKzKFxa/5tpERKoy\n9VyIiNQAI0aM4O6772bLli0cP36cqKgoRo0ahcPhIDMzk5EjRzJv3jwCAwMBmD9/PoWFhSQkJLjX\nDx8+nL/97W/k5+dz11138Zvf/Ibp06ezf/9+oqKieO655wgJCXGfc8+ePfzlL38hLy+PmJgYhg0b\nRq1atQA4efIk8+fPZ//+/fj7+9OzZ08efPBBADZu3Mhnn31Gx44d+fLLL2ndujWjR4++4Jp27tzJ\nkiVLyMjIoF69ejz66KNER0fz+eefs2jRIpxOJ08++SSdO3cmISHhgv0PHjzI/PnzOX78OA6Hgwcf\nfJDbbrvNvX7z5s38/e9/JyMjg6CgIOLi4ujevfsl182YMYPatWvz5JNPAlBYWMigQYN4//33CQsL\nY8aMGZjNZoqKiti5cycDBgzgnnvuISkpiY8//pisrCwaNGjAwIEDadmyJQATJ06kRYsWHD58mB9+\n+IEGDRowYsQIrrvuOgCKiopYsmQJ27dvp7CwkMjISF588UUcDgfFxcUsXryY7du3U1paSvv27Rk0\naBCBgYGUlZUxa9Ystm/fTnl5OWFhYSQkJBAVFXXVv28iUnOpuBARqSE2bdrE2LFjsdvtTJkyhWXL\nll30Q/cv2bNnD1OnTiUzM5M//OEP/PDDDzz99NPUq1eP119/ndWrVzNw4ECP8/3xj3/EZrPxl7/8\nhXnz5pGQkEBJSQmTJk3iN7/5DWPGjOHUqVNMnjyZ0NBQ7rzzTgCOHTvGLbfcwgcffHDRu/snT55k\nypQpPPvss9x8880kJyfz5ptv8vbbb9OnTx9q1arF559/zhtvvHHRayksLOTPf/4zcXFx9O7dm9TU\nVF5//XXCw8Np2bIl27ZtY968ebzwwgvccMMN5Ofnk5OTA3DJdRWRlJTEmDFjeP755ykpKeG7775j\n0aJFjB07lqZNm5KcnMwbb7zBu+++S1BQkDvLl156iUaNGpGYmMjcuXOZMGECAO+//z6lpaX8+c9/\nxm63c+TIEWw2GwAzZszAarUydepULBYLH374IXPnzmXkyJFs3LiRY8eOMX36dGrVqkV6erp7PxGR\nX0vDokREaoi7776bsLAw/Pz86Nq1K4cPH76i/R966CFsNhsNGzakSZMmtG7dmoYNG+Ln50enTp0u\nON7999+P3W4nMDCQ+Ph4kpKSANi+fTtBQUHce++9mM1m6tatS58+fdi8e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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10abdf350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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99poaNmyo3/72t44xTp06JYvFolOnTqmwsFDJycmSpAYNGsjT09PRb926dSos\nLFSfPn1KdI4AAAAAbo3gDRhk//79io2Nlclkkslk0uTJkyVJsbGxeu2115SSkqI1a9YoJydH999/\nv6KiohQXFyd3d3fHGG+99ZbWrFnjeN29e3dJ0urVq9WuXTtH+8qVKxUTE6MaNWqU0OwAAAAA3C6T\n/UYPGMYdycjIkM1mc3UZwD27YDPrmcRDri6jxMx/PFT+Hnd3F3kAruXr66vMzExXlwEAN8Wxqvxy\nd3eXv7//bfXlGm8AAAAAAAxE8AYAAAAAwEAEbwAAAAAADETwBgAAAADAQNzVHLgF97xcKS/X1WWU\nGHtVP1eXAAAAAJQrBG/gVvJylf/8UFdXUXJmfOzqCgAAAIByhVPNAQAAAAAwEMEbAAAAAAADEbwB\nAAAAADAQwRsAAAAAAAMRvAEAAAAAMBDBGwAAAAAAAxG8AQAAAAAwEMEbAAAAAAADEbwBAAAAADAQ\nwRsAAAAAAAMRvAEAAAAAMBDBGwAAAAAAAxG8AQAAAAAwEMEbAAAAAAADEbwBAAAAADAQwRsAAAAA\nAAMRvAEAAAAAMBDBGwAAAAAAAxG8AQAAAAAwEMEbAAAAAAADEbwBAAAAADAQwRsAAAAAAAMRvAEA\nAAAAMBDBGwAAAAAAAxG8AQAAAAAwEMEbAAAAAAADEbwBAAAAADAQwRsAAAAAAAMRvAEAAAAAMBDB\nGwAAAAAAAxG8AQBAhZKUlKQhQ4aoZcuWCggI0ObNm522T58+XVFRUWrcuLHCw8PVr18/7d2716nP\ngQMH9OSTTyosLEwPPvig/vGPf8hqtTr12bdvn/r27auwsDCFh4drwIABOnTokOHzAwCUPgRvAABQ\noVitVoWHhys+Pl4mk+ma7Y0aNVJ8fLy2bt2qtWvXql69eurfv78yMzMlSWfPnlW/fv3UsGFDbdiw\nQR9++KEOHz6sv/3tb07vMXDgQNWrV08bNmzQ2rVr5eXlpYEDB6qwsLDE5goAKB0quboAAACAkhQd\nHa3o6GhJkt1uv2Z77969nV5PmjRJK1asUEpKijp06KAvvvhClStXVnx8vKPP1KlT1aVLF6Wnpyso\nKEhHjx5Vdna2xo0bp9q1a0uSxo4dq0cffVQnT55UUFCQgTMEAJQ2rHgDAADcgM1m07Jly+Tt7a2w\nsDBJ0uXLl+Xu7u7Ur0qVKpKknTt3Srqyal6zZk2tXLlSNptNeXl5Wr58uUJCQlSvXr2SnQQAwOUI\n3gAAAL+tT9XbAAAgAElEQVTyxRdfKCQkRA0bNtT8+fO1YsUK1axZU5LUoUMHZWRk6L333pPNZpPF\nYtGUKVNkMpl07tw5SZKXl5dWr16tNWvWqFGjRgoNDdVXX32lpUuXymzm4xcAVDQc+QEAAH6lQ4cO\n+vzzz7V+/XpFR0dr+PDhjmu8Q0JCNGPGDM2dO1fBwcFq2bKlgoKC5OfnJzc3N0lSfn6+xo0bp7Zt\n2+rTTz/VunXrFBoaqkGDBunSpUuunBoAwAW4xhsAAOBXqlatqqCgIAUFBalFixbq2LGjVqxYoVGj\nRkm6ch147969deHCBXl6ekqS3n//fQUGBkqSPv74Y506dUobNmxwjDlr1iyFhYVp06ZN6tWrV8lP\nCgDgMqx4AwAA3ILdbtfly5evab/vvvtUtWpVrVu3Th4eHnrkkUckXVnx/vUp5SaTSSaT6bo3dAMA\nlG+lcsU7JSVF69evV2pqqiwWi+Li4tSqVavr9p07d662bNmiwYMHKyYmxtF+8eJFLVy4UHv27JHZ\nbFbbtm01ZMgQeXh4OPqkp6dr4cKFOnr0qLy9vdW9e3e+gQYAoJyzWq06fvy4IwCnp6crOTlZPj4+\n8vX11dtvv62uXbvq/vvvV2ZmphYtWqQzZ87osccec4yxePFitWrVSp6envrqq6/06quv6qWXXlL1\n6tUlSY888oheffVVjR8/Xs8884wKCws1a9Ysubu76+GHH3bJvAEArlMqg/elS5dUv359RUdHa9q0\naTfst3PnTh09elS+vr7XbJs5c6ays7M1ceJEFRQU6N1339XcuXM1evRoSVJeXp7i4+MVERGhYcOG\n6ccff9ScOXPk5eWlzp07GzY3AADgWvv371dsbKxjBXry5MmSpNjYWE2ZMkXHjh3Tn/70J2VlZcnH\nx0eRkZFau3atGjdu7Bhj7969mjZtmqxWqxo1aqQ333xTffr0cWwPDg7W4sWLlZCQoN69e8tkMqlZ\ns2b68MMP5e/vX+JzBgC4VqkM3pGRkYqMjLxpn6vfQE+YMEFTpkxx2nbq1Cnt379fU6dOVYMGDSRJ\nTz/9tKZOnapBgwbJx8dHX3/9tQoLCzVixAi5ubkpICBAaWlp2rBhA8EbAIByrH379jp58uQNt8+b\nN++WY7z99tu37PPII484Tj0HAFRsZfIab7vdrlmzZql3794KCAi4Zvvhw4fl5eXlCN2SFBERIZPJ\npCNHjjj6NG3a1HH3UUlq3ry5Tp8+LavVavwkAAAAAAAVQpkM3mvXrlWlSpXUvXv36263WCzy9vZ2\najObzapWrZosFoskKTs7+5o+V19f7QMAAAAAwL0qc8E7NTVVGzdu1MiRI+94X7vdLpPJZEBVAAAA\nAABcX6m8xvtmvv/+e+Xk5GjEiBGOtqKiIi1dulT/+c9/NGvWLPn4+Cg7O9tpv6KiIuXm5srHx0fS\nldXtX/e5+vpqnztRo0YNHg9STlmzL7i6BBjI7OYmX987/5kH4Hru7u7XvcEqgPJp27ZtmjFjhr79\n9ludOXNGiYmJTk8biI+P1+rVq3Xy5ElVrlxZLVq00Msvv6zWrVs7jbNx40ZNmTJFBw8edDwGcNWq\nVZKu3Efq6aef1oEDB5SZmSl/f3899thjmjx5suOpBXeKY1X5dSeLumUueP/mN79RRESEU9urr76q\n3/zmN4qOjpYkhYSEKDc3V8ePH3dc533gwAHZ7XYFBwc7+qxatUpFRUWO52zu379fderUkaen5x3X\nlZOTI5vNdi9TQynlXljo6hJgoKLCQmVmZrq6DAB34bK5srKtl1xdRonxdDfLy40v+VFxnT17Vo0b\nN9Yf/vAHDRs2TBcvXnT6HV6nTh1NnjxZQUFBys/P19y5c/XYY49p+/btjuD76aef6h//+IfGjx+v\nGTNmqKCgQN9//71jnOzsbHXq1Eljx46Vr6+v0tLSNH78eJ07d07vvPPOXdXt6+vLZ41yyt3d/baf\nVFEqg3d+fr7OnDnjeH327FmlpaWpWrVq8vPzU7Vq1Zz6u7m5ycfHR7Vr15Yk1a1bV5GRkXr//fc1\ndOhQFRQUaOHCherQoYNjNbtjx4766KOP9O677+r3v/+9fvzxR23cuFFPP/10yU0UAADctZ8vFWjo\nRz+4uowSM//xUHm5cckcKq7o6GjHQtv1zjTt3bu30+tJkyZpxYoVSklJUYcOHVRYWKhJkyZp4sSJ\n6tu3r6Pf1YU56cpZsU899ZTjdd26dTV48GC99957xT0dVDClMninpqbqlVdecbxeunSpJCkqKuq6\n13Zfb4l/9OjRWrBggf71r3/JbDarbdu2TqHa09NTEyZM0IIFC/TCCy+oevXqio2NVadOnQyYEQAA\nAICSYrPZtGzZMnl7eyssLEzSlTNgz549K0nq1q2bMjIyFB4ern/+858KCQm57jhnzpzRf/7zH7Vv\n377Eakf5VCqDd1hYmOM6i9sxa9asa9q8vLw0evTom+4XGBjoFPABAAAAlF1ffPGFRo4cqby8PN1/\n//1asWKFatasKUlKT0+X3W5XQkKCXn75ZQUEBOi9997T448/rm3btjk98WjUqFHatGmT8vPz1bVr\nV7355puumhLKiTJ3V3MAAAAAuJ4OHTro888/1/r16xUdHa3hw4c7rq++enr6c889p+7du6tZs2aa\nPn26TCaTNmzY4DTOK6+8ok2bNmnhwoVKT0/Xyy+/XNJTQTlD8AYAAABQLlStWlVBQUFq0aKF3nzz\nTbm5uWnFihWSpFq1aklyvqa7cuXKCgwM1KlTp5zG8fPzU6NGjdS1a1dNnTpVS5cuVUZGRslNBOUO\nwRsAAABAuWS323X58mVJUkREhKpUqaLU1FTHdpvNppMnTyogIOCGYxQWFspkMjnGAe5GqbzGGwAA\nAAB+yWq16vjx445TxtPT05WcnCwfHx/5+vrq7bffVteuXXX//fcrMzNTixYt0pkzZxzP+q5WrZoG\nDhyot956S7Vr11bdunU1Z84cmUwmR5+tW7cqIyNDkZGR8vLy0vfff6/4+Hi1adNGdevWddncUfYR\nvAEAAACUevv371dsbKxMJpNMJpMmT54sSYqNjdWUKVN07Ngx/elPf1JWVpZ8fHwUGRmptWvXqnHj\nxo4xJk6cKHd3dz333HPKz89XixYtlJiYqBo1akiSPDw8tHz5ck2ePFmXLl1SnTp1FBMTo1GjRrlk\nzig/TPbrPQQPdywjI0M2m83VZcAA7pnnlP/8UFeXUWKyZnysZ9cecXUZJWb+46Hy9+C5uEBZdMFm\n1jOJh1xdRonheAWUTb6+vo4bvKF8cXd3l7+//2315RpvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAxE\n8AYAAAAAwEDc1RwAAABAiXHPy5Xycl1dRonJL7gsVars6jLgYgRvAAAAACUnL7dCPTHG7a1Fkvd9\nri4DLsap5gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI\n3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAA\nGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAA\nAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACAgQje\nAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAY\niOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAA\nAICBCN4AAAAAABiI4A0AAAAApUxSUpKGDBmili1bKiAgQJs3b3ZsKygoUHx8vLp06aLGjRurZcuW\neu6553T27FmnMWbOnKnevXsrODhY4eHh17xHYmKiAgICVK9ePQUEBDj+1KtXT5mZmYbPsSIheAMA\nAABAKWO1WhUeHq74+HiZTCanbXl5eUpOTtaYMWO0adMmzZ8/X8eOHdMzzzzj1K+goEA9e/bUoEGD\nrvsevXv31r59+7R3717t27dP+/bt029/+1u1b99evr6+hs2tIqrk6gIAAAAAAM6io6MVHR0tSbLb\n7U7bqlevruXLlzu1xcfH67HHHtPp06dVp04dSdLYsWMlXVnZvp4qVaqoSpUqjteZmZnavn27pk+f\nXmzzwBWseAMAAABAGZednS2TySRvb++7HiMxMVGenp6KiYkpxsogEbwBAAAAoEy7dOmSpkyZot//\n/vfy8vK663ESExPVp08fp1VwFA+CNwAAAACUUQUFBRo+fLhMJpOmTJly1+Ps3r1bR44cUb9+/Yqx\nOlzFNd4AAAAAUAZdDd2nT59WYmLiPa12r1ixQuHh4WrWrFkxVoirWPEGAAAAgDLmauhOT0/XqlWr\n5OPjc9djWa1WbdiwQU8++WQxVohfYsUbAAAAAEoZq9Wq48ePO+5onp6eruTkZPn4+OiBBx7QsGHD\nlJycrCVLlqigoEAZGRmSJB8fH7m7u0uSTp06JYvFolOnTqmwsFDJycmSpAYNGsjT09PxXuvWrVNh\nYaH69OlTwrOsOAjeAAAAAFDK7N+/X7GxsTKZTDKZTJo8ebIkKTY2VmPHjtXnn38uk8mkrl27Srry\nyDGTyaTVq1erXbt2kqS33npLa9ascYzZvXt3SXLqI0krV65UTEyMatSoUVLTq3AI3gAAAABQyrRv\n314nT5684fabbbsqISFBCQkJt+y3bt26O6oNd45rvAEAAAAAMBDBGwAAAAAAAxG8AQAAAAAwEMEb\nAAAAAAADcXM1AAAAADBIloe3LubbXV1GifF0N8vLreLM93aVyuCdkpKi9evXKzU1VRaLRXFxcWrV\nqpUkqbCwUCtWrNC+fft09uxZeXp66sEHH9SAAQNUs2ZNxxgXL17UwoULtWfPHpnNZrVt21ZDhgyR\nh4eHo096eroWLlyoo0ePytvbW927d1evXr1KfL4AAAAAyqfcApOGrv3B1WWUmPmPh8rLzeTqMkqd\nUnmq+aVLl1S/fn09++yz192Wnp6uJ554Qm+88Ybi4uL0008/6Y033nDqN3PmTJ06dUoTJ07UCy+8\noJSUFM2dO9exPS8vT/Hx8fL399frr7+ugQMHavXq1dqyZYvh8wMAAAAAVBylcsU7MjJSkZGR193m\n6empCRMmOLU988wzGj9+vC5cuKD77rtPJ0+e1P79+zV16lQ1aNBAkvT0009r6tSpGjRokHx8fPT1\n11+rsLBQI0aMkJubmwICApSWlqYNGzaoc+fOhs8RAAAAAFAxlMoV7zuVm5srk8kkLy8vSdKRI0fk\n5eXlCN2SFBERIZPJpCNHjkiSDh8+rKZNm8rNzc3Rp3nz5jp9+rSsVmvJTgAAAAAAUG6V+eBts9m0\nfPlydezY0XH9tsVikbe3t1M/s9msatWqyWKxSJKys7Ov6XP19dU+AAAAAADcqzIdvAsLCzV9+nSZ\nTCYNHTr0lv3tdrtMJi70BwAAAACUnFJ5jfftuBq6L1y4oIkTJzrdrdzHx0fZ2dlO/YuKipSbmysf\nHx9JV1a3f93n6uurfe5EjRo1ZLdz2/zyyJp9wdUlwEBmNzf5+t75zzwA18s8m33rTuUIxyuUF3y2\nKt8q0rHqThZ1y2Twvhq6z507p0mTJqlatWpO20NCQpSbm6vjx487rvM+cOCA7Ha7goODHX1WrVql\noqIimc1XFv7379+vOnXqyNPT845rysnJkc1mu8eZoTRyLyx0dQkwUFFhoTIzM11dBoC7YC/bJ+7d\nMY5XKC/4bFW+VaRjlbu7u/z9/W+rb6n8jZWfn6+0tDSlpaVJks6ePau0tDSdP39eRUVFmjZtmo4f\nP66//vWvKigokMVikcViUUFBgSSpbt26ioyM1Pvvv6+jR4/q+++/18KFC9WhQwfHanbHjh1VqVIl\nvfvuuzp58qT+97//aePGjerZs6erpg0AAAAAKIdK5Yp3amqqXnnlFcfrpUuXSpKioqIUGxurPXv2\nSJLi4uKc9ps0aZLCwsIkSaNHj9aCBQv0r3/9S2azWW3bttXTTz/t6Hv1sWQLFizQCy+8oOrVqys2\nNladOnUyenoAAAAAgAqkVAbvsLAwrVq16obbb7btKi8vL40ePfqmfQIDA50CPgAAAAAAxa1UnmoO\nAAAAAEB5QfAGAAAAAMBABG8AAAAAAAxE8AYAAAAAwEAEbwAAAAAADETwBgAAAADAQARvAAAAAAAM\nRPAGAAAAAMBABG8AAAAAAAxE8AYAAAAAwEAEbwAAAAAADETwBgAAAADAQARvAAAAAAAMRPAGAAAA\nAMBABG8AAAAAAAxE8AYAAAAAwEAEbwAAAAAADETwBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8A\nAAAAAAxE8AYAAAAAwEAEbwAAAAAADETwBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAxE\n8AYAAAAAwEAEbwAAAAAADETwBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAxE8AYAAAAA\nwEAEbwAAAAAADETwBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAxE8AYAAAAAwEAEbwAA\nAAAADETwBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAxE8AYAAAAAwEAEbwAAAAAADETw\nBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAxE8AYAAAAAwEAEbwAAAAAADETwBgAAAADA\nQARvAAAAAAAMRPAGAKCCS0pK0pAhQ9SyZUsFBARo8+bN1/R588039dBDD6lRo0bq16+fjh8/7rR9\n5syZ6t27t4KDgxUeHn7d95k4caJ69Oihhg0bqlu3bobMBQCA0ojgDQBABWe1WhUeHq74+HiZTKZr\nts+ePVuLFy/W1KlT9emnn8rT01MDBgzQ5cuXHX0KCgrUs2dPDRo06Kbv1a9fP/Xq1avY5wAAQGlW\nydUFAAAA14qOjlZ0dLQkyW63X7N9wYIFeu6559S1a1dJ0ttvv63IyEh99tlnjhA9duxYSVJiYuIN\n32fy5MmSpAsXLiglJaVY5wAAQGnGijcAALihH3/8UefOnVPHjh0dbdWrV1eLFi20Z88eF1YGAEDZ\nQfAGAAA3dO7cOZlMJvn7+zu1+/n5KSMjw0VVAQBQthC8AQDAHbPb7de9HhwAAFyL4A0AAG6oVq1a\nstvt16xuX7hwQX5+fi6qCgCAsoXgDQAAbigwMFC1atXStm3bHG0///yz9u7dq1atWrmwMgAAyg7u\nag4AQAVntVp1/Phxxx3N09PTlZycLB8fH9WtW1dDhw7V22+/rfr166tevXp688039cADDzg9i/vU\nqVOyWCw6deqUCgsLlZycLElq0KCBPD09JUlpaWm6ePGizp49q/z8fEef0NBQVarERxIAQPnFbzkA\nACq4/fv3KzY2ViaTSSaTyfHYr9jYWE2fPl0jR45UXl6eXnjhBWVnZ6tt27ZatmyZKleu7Bjjrbfe\n0po1axyvu3fvLklavXq12rVrJ0n6+9//rqSkpGv6fPPNN6pbt67h8wQAwFUI3gAAVHDt27fXyZMn\nb9pn3LhxGjdu3A23JyQkKCEh4aZj/DKYAwBQkXCNNwAAAAAABiJ4AwAAAABgoFJ5qnlKSorWr1+v\n1NRUWSwWxcXFXXPn1FWrVmnr1q3Kzc1VaGiohg0bpgceeMCx/eLFi1q4cKH27Nkjs9mstm3basiQ\nIfLw8HD0SU9P18KFC3X06FF5e3ure/fu6tWrV4nNEwAAAABQ/pXK4H3p0iXVr19f0dHRmjZt2jXb\n165dq88++0yjRo1SrVq1tHLlSsXHxyshIcFxV9SZM2cqOztbEydOVEFBgd59913NnTtXo0ePliTl\n5eUpPj5eERERGjZsmH788UfNmTNHXl5e6ty5c4nOFwCA4uCelyvl5bq6jBJjr8pzxAEAZUOpDN6R\nkZGKjIy84faNGzfq8ccfd6yC/+Uvf9GwYcO0c+dOPfzwwzp58qT279+vqVOnqkGDBpKkp59+WlOn\nTtWgQYPk4+Ojr7/+WoWFhRoxYoTc3NwUEBCgtLQ0bdiwgeANACib8nKV//xQV1dRcmZ87OoKAAC4\nLWXuGu9z587JYrHowQcfdLR5enqqcePGOnz4sCTpyJEj8vLycoRuSYqIiJDJZNKRI0ckSYcPH1bT\npk3l5ubm6NO8eXOdPn1aVqu1hGYDAAAAACjvylzwtlgskiRvb2+ndm9vb8c2i8VyzXaz2axq1ao5\n+mRnZ193jF++BwAAAAAA96rMBe8bsdvtMplM99wHAAAAAIDiVCqv8b4ZHx8fSVdWrK/+XZJycnJU\nv359R5/s7Gyn/YqKipSbm+vYx9vb+5o+V1//ctzbVaNGDdnt9jveD6WfNfuCq0uAgcxubvL1vfOf\neaA04nhVvnG8QnnBsap8q0jHqjtZ1C1zwbtWrVry8fHRgQMHFBQUJEmyWq06cuSIunXrJkkKCQlR\nbm6ujh8/7rjO+8CBA7Lb7QoODnb0WbVq1f/X3r2HeV3XeR9/zTADw4DDyEnjpKKAoSibBzINWPPO\nPJSViVtmJkmZldVtu55W07yp3e617na11hSkvXM3PACV3rDrITEjDygaSgoICMiiIgyjDChzuP/o\n8rc74QFwvg4zPB7XxXU53+/n95v3d66rT9dzvr/fb9Lc3Jzy8j/d+H/88cczYMCAVFdX7/Bc9fX1\n2bp1a1tcIruYyqam9h6BAjU3NWX9+vXtPQa0CftV52a/orOwV3Vuu9NeVVlZmX79+m3X2l3ypeZb\ntmzJihUrsmLFiiTJ888/nxUrVmTdunVJkhNPPDEzZszI/Pnzs3LlylxzzTXp06dPjjjiiCTJwIED\nM3r06Fx33XVZunRpnnrqqUydOjVHH3106W72Mccck4qKivz4xz/O6tWrM2/evMyePTsf/ehH2+Wa\nAQAA6Jx2yTvey5Yty5VXXln6+l/+5V+SJOPGjct5552XU045Ja+++mquv/76bNq0Ke9973tzySWX\nlP6Gd5Kcf/75mTJlSq666qqUl5dnzJgxOfvss0vnq6urc+mll2bKlCm56KKLsscee+S0007Lscce\n++5dKAAAAJ3eLhneI0eOzPTp099yzYQJEzJhwoQ3Pd+jR4+cf/75b/kcQ4YMaRX4AAAA0NZ2yZea\nAwAAQGchvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAK\nJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAAClSxsw9c\nuHBhli9fno997GOlY/fcc09uueWWNDY25uijj87nPve5lJdrewAAAHZfO13Ft9xyS1asWFH6euXK\nlbn++utTU1OTkSNHZvbs2fnVr37VFjMCAABAh7XT4f3cc89l//33L3193333pXv37vnOd76Tb37z\nm/nQhz6U++67r02GBAAAgI5qp8N7y5Yt6d69e+nrxx57LKNHj063bt2SJAcccEBefPHFdz4hAAAA\ndGA7Hd59+/bNM888kyRZu3ZtVq1alUMOOaR0/pVXXkllZeU7nxAAAAA6sJ3+cLVjjjkmt956a9av\nX5/Vq1enR48eOeKII0rnly1blve85z1tMiQAAAB0VDsd3p/85CfT2NiYBQsWpG/fvjnvvPPSo0eP\nJH+62/3kk0/mxBNPbLNBAQAAoCPa6fDu0qVLPv3pT+fTn/70Nud69uyZ66+//h0NBgAAAJ1Bm/yR\n7Q0bNmTFihXZsmVLWzwdAAAAdBrvKLwffvjhfOMb38i5556bCy+8MEuXLk2S1NfX52/+5m/y0EMP\ntcmQAAAA0FHtdHjPnz8///AP/5A99tgjp512WqtzNTU16d27d+699953Oh8AAAB0aDsd3rfddltG\njhyZq666Kscff/w254cPH57ly5e/o+EAAACgo9vp8F65cmWOOuqoNz3fq1ev1NfX7+zTAwAAQKew\n0+HdrVu3t/wwteeffz49e/bc2acHAACATmGnw/uggw7K3Llz09TUtM25urq63H333Tn00EPf0XAA\nAADQ0e10eH/605/O+vXrc/HFF+fOO+9Mkjz22GP5xS9+kQsuuCBJ8qlPfaptpgQAAIAOqmJnHzhg\nwIB85zvfybRp0zJ9+vQkya9//eskyciRI/OFL3wh/fv3b5spAQAAoIPa6fBOksGDB+eyyy7LK6+8\nkrVr16alpSV77bVXampq2mo+AAAA6NB2OrzXrVuXqqqq9OzZMz179swBBxzQ6vxrr72W+vr69O3b\n9x0PCQAAAB3VTr/H+ytf+Uq+/OUv57e//e0bnn/wwQfzla98ZacHAwAAgM5gp8M7SWpqanLNNddk\n2rRpaW5ubquZAAAAoNN4R+/xfv2Tzf/t3/4tzz77bL75zW96fzcAAAD8N+/ojneSfOxjH8ull16a\n1atX56KLLsozzzzTFnMBAABAp/COwztJDj744Pzd3/1d9txzz3z729/Ovffe2xZPCwAAAB3eO3qp\n+X/Xp0+fXHnllZk6dWp+8pOfZNCgQW311AAAANBhtckd79dVVFTki1/8Ys4999ysXbu2LZ8aAAAA\nOqSdvuM9ffr0Nz33l3/5lzn88MOzZcuWnX16AAAA6BTa7KXmf26PPfbIHnvsUdTTAwAAQIew3eH9\n4x//OGVlZfnSl76U8vLy/PjHP37bx5SVleXLX/7yOxoQAAAAOrLtDu8nn3wyZWVlaW5uTnl5eZ58\n8sm3fUxZWdk7Gg4AAAA6uu0O72uvvfYtvwYAAAC21Wbv8X7uuefy+9//PnV1dRkwYEDGjx+f6urq\ntgZi2qkAACAASURBVHp6AAAA6JB2KLznzJmT2bNn56qrrkpNTU3p+Pz58/PDH/4wjY2NpWOzZ8/O\n5MmTW60DAACA3c0O/R3v+fPnZ6+99moV001NTbnuuutSXl6eL3/5y/mHf/iHfOYzn8m6desyY8aM\nNh8YAAAAOpIdCu/Vq1dn2LBhrY49+eSTqa+vz0knnZTx48dn8ODBOeWUU3LUUUdlwYIFbTosAAAA\ndDQ7FN4vv/xy+vTp0+rYwoULkyRHHnlkq+MjRozIunXr3uF4AAAA0LHtUHjX1tamrq6u1bGnnnoq\n3bp1yz777NPqeEVFRSoq2uyz2wAAAKBD2qHwHjp0aObOnZvNmzcnSVatWpWlS5fm0EMPTZcuXVqt\nfe6557a5Ow4AAAC7mx26JX3aaafl4osvzvnnn5/Bgwdn2bJlSZKPf/zj26x9+OGHc9BBB7XNlAAA\nANBB7dAd7yFDhuTyyy/P0KFDs2HDhgwbNiwXX3xx9t9//1brnnzyyXTt2jVHHXVUmw4LAAAAHc0O\nvwl7xIgRufjii99yzUEHHZSrr756p4cCAACAzmKH7ngDAAAAO0Z4AwAAQIGENwAAABRIeAMAAECB\nhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBKtp7gJ3R3Nycm2++Offff3/q\n6uqy5557Zvz48Tn11FNbrZs+fXruueeebNq0KSNGjMikSZOy9957l86/8sormTp1ah555JGUl5dn\nzJgx+fznP5+qqqp3+5IAAADopDrkHe9Zs2blrrvuyjnnnJP/83/+Tz772c/mV7/6VebMmdNqzZw5\nczJp0qR897vfTbdu3TJ58uQ0NjaW1vzjP/5jnnvuuVx++eW56KKL8sc//jE//elP2+OSAAAA6KQ6\nZHgvXrw4hx9+eEaPHp2+fftmzJgxOeSQQ7J06dLSmtmzZ+fUU0/N4YcfniFDhuSrX/1q1q9fn4ce\neihJsnr16jz++OM599xzs//++2fEiBE5++yzM2/evNTV1bXXpQEAANDJdMjwHjFiRJ544on853/+\nZ5JkxYoVefrpp/MXf/EXSZIXXnghdXV1GTVqVOkx1dXVGTZsWBYvXpwkWbJkSXr06JH99tuvtOaQ\nQw5JWVlZlixZ8i5eDQAAAJ1Zh3yP98c//vFs3rw53/jGN1JeXp6Wlpb81V/9VY4++ugkKd2x7tWr\nV6vH9erVq3Surq5um/Pl5eXp2bOnO94AAAC0mQ4Z3vPmzcv999+fb3zjGxk0aFBWrFiRadOmpXfv\n3hk7duybPq6lpSXl5W99k7+lpSVlZWVtPTIAAAC7qQ4Z3j//+c/ziU98IkcddVSSZPDgwXnxxRcz\nc+bMjB07NrW1tUmSjRs3lv47Serr67PvvvsmSWpra7Nx48ZWz9vc3JxNmzZtcyd8e9TU1KSlpWUn\nr4hdWcPGl9p7BApU3qVLeveuffuF0AHYrzo3+xWdhb2qc9ud9qoduWHbIcP7tdde2+Yiy8rKSuHb\nv3//1NbWZuHChdlnn32SJA0NDVmyZEmOP/74JMnw4cOzadOmLF++vPQ+74ULF6alpSXDhg3b4Znq\n6+uzdevWd3JZ7KIqm5raewQK1NzUlPXr17f3GNAm7Fedm/2KzsJe1bntTntVZWVl+vXrt11rO2R4\nH3bYYZkxY0b69OmTwYMHZ/ny5bnjjjty7LHHltaceOKJmTFjRvbee+/0798/v/jFL9KnT58cccQR\nSZKBAwdm9OjRue6663LOOeeksbExU6dOzdFHH93qLjkAAAC8Ex0yvCdOnJjp06dnypQpqa+vz557\n7pkPf/jDOfXUU0trTjnllLz66qu5/vrrs2nTprz3ve/NJZdckoqK/7rk888/P1OmTMlVV12V8vLy\njBkzJmeffXZ7XBIAAACdVIcM76qqqpx11lk566yz3nLdhAkTMmHChDc936NHj5x//vltPR4AAACU\ndMi/4w0AAAAdhfAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglv\nAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ\n8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACA\nAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAA\nACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAG\nAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJ\nbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAo\nkPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAlW09wA7a/369bnp\nppvy2GOP5dVXX8173vOefPnLX87QoUNLa6ZPn5577rknmzZtyogRIzJp0qTsvffepfOvvPJKpk6d\nmkceeSTl5eUZM2ZMPv/5z6eqqqo9LgkAAIBOqEPe8d60aVMuu+yyVFZW5tJLL80Pf/jDnHnmmenZ\ns2dpzaxZszJnzpxMmjQp3/3ud9OtW7dMnjw5jY2NpTX/+I//mOeeey6XX355Lrroovzxj3/MT3/6\n0/a4JAAAADqpDhnes2bNSt++fXPuuedm6NCh6devXw455JD079+/tGb27Nk59dRTc/jhh2fIkCH5\n6le/mvXr1+ehhx5KkqxevTqPP/54zj333Oy///4ZMWJEzj777MybNy91dXXtdWkAAAB0Mh0yvB95\n5JHsv//++cEPfpBJkyblwgsvzN133106/8ILL6Suri6jRo0qHauurs6wYcOyePHiJMmSJUvSo0eP\n7LfffqU1hxxySMrKyrJkyZJ372IAAADo1Drke7yff/75/Md//EdOPvnkfPKTn8zSpUtz4403prKy\nMmPHji3dse7Vq1erx/Xq1at0rq6ubpvz5eXl6dmzpzveAAAAtJkOGd4tLS3Zf//981d/9VdJkn33\n3TerVq3KnXfembFjx77l48rL3/omf0tLS8rKytp0XgAAAHZfHTK899xzzwwcOLDVsYEDB5bev11b\nW5sk2bhxY+m/k6S+vj777rtvac3GjRtbPUdzc3M2bdq0zZ3w7VFTU5OWlpYdfhy7voaNL7X3CBSo\nvEuX9O5d+/YLoQOwX3Vu9is6C3tV57Y77VU7csO2Q4b3iBEjsmbNmlbH1qxZk759+yZJ+vfvn9ra\n2ixcuDD77LNPkqShoSFLlizJ8ccfnyQZPnx4Nm3alOXLl5fe571w4cK0tLRk2LBhOzxTfX19tm7d\n+k4ui11UZVNTe49AgZqbmrJ+/fr2HgPahP2qc7Nf0VnYqzq33WmvqqysTL9+/bZrbYf8cLWTTjop\nS5YsycyZM7N27drcf//9ueeee/KRj3yktObEE0/MjBkzMn/+/KxcuTLXXHNN+vTpkyOOOCLJn+6Q\njx49Otddd12WLl2ap556KlOnTs3RRx/d6i45AAAAvBMd8o73/vvvn29961v513/919x2223p379/\nPv/5z+foo48urTnllFPy6quv5vrrr8+mTZvy3ve+N5dcckkqKv7rks8///xMmTIlV111VcrLyzNm\nzJicffbZ7XFJAAAAdFIdMryT5H3ve1/e9773veWaCRMmZMKECW96vkePHjn//PPbejQAAAAo6ZAv\nNQcAAICOQngDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAA\nFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMA\nAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3\nAAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRI\neAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABA\ngYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAA\nABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgD\nAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFKiivQdoCzNn\nzswvfvGLnHjiiTnrrLOSJFu3bs3Pfvaz/P73v8/WrVtz6KGH5pxzzkmvXr1Kj1u3bl2uv/76LFq0\nKFVVVRk3blw+85nPpLzc7yMAAABoGx2+MJcuXZq77747++yzT6vj06ZNy4IFC3LBBRfkyiuvzIYN\nG3L11VeXzjc3N+d73/tempubM3ny5HzlK1/Jvffem5tvvvndvgQAAAA6sQ4d3lu2bMk//dM/5dxz\nz02PHj1KxxsaGvKb3/wmZ511VkaOHJn99tsv5513Xp5++uksXbo0SfL4449nzZo1+drXvpYhQ4Zk\n9OjROf300/Pv//7vaWpqaq9LAgAAoJPp0OF9ww035LDDDsvBBx/c6viyZcvS1NTU6viAAQPSt2/f\nLF68OEmyZMmSDBkyJDU1NaU1hx56aBoaGrJq1ap35wIAAADo9DpseP/ud7/Ls88+m8985jPbnKur\nq0tFRUWqq6tbHe/Vq1fq6upKa/77+72TpLa2tnQOAAAA2kKH/HC1l156KdOmTctll12Wiortv4SW\nlpbtWldWVrbDM9XU1Gz389OxNGx8qb1HoEDlXbqkd+/a9h4D2oT9qnOzX9FZ2Ks6t91pr9qRbuyQ\n4b1s2bLU19fnwgsvLB1rbm7OokWLMmfOnFx66aVpbGxMQ0NDq7ve9fX1pbvatbW1eeaZZ1o97+t3\nuv/8Tvj2qK+vz9atW3fmctjFVXrPf6fW3NSU9evXt/cY0CbsV52b/YrOwl7Vue1Oe1VlZWX69eu3\nXWs7ZHiPGjWq1SeUJ8m1116bgQMH5uMf/3h69+6dLl265IknnsiRRx6ZJFmzZk3WrVuX4cOHJ0mG\nDx+emTNnpr6+vvQ+7z/84Q+prq7OoEGD3t0LAgAAoNPqkOFdVVW1TRxXVVVljz32KB0/9thj87Of\n/Sw9evRI9+7dc+ONN2bEiBE54IADkiSHHHJIBg0alGuuuSZnnHFGNmzYkOnTp+f444/foZevAwAA\nwFvptIV51llnpby8PD/4wQ+ydevWjB49Ol/4whdK58vLy3PhhRfmhhtuyN/+7d+mqqoq48aNy4QJ\nE9pxagAAADqbThPe3/72t1t9XVlZmYkTJ2bixIlv+pi+ffvmoosuKno0AAAAdmMd9s+JAQAAQEcg\nvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACg\nQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAA\nAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwB\nAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDC\nGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAK\nJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAA\noEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsA\nAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAFe09wM6YOXNmHnrooaxZsyZdu3bN\n8OHDc8YZZ2TAgAGlNVu3bs3Pfvaz/P73v8/WrVtz6KGH5pxzzkmvXr1Ka9atW5frr78+ixYtSlVV\nVcaNG5fPfOYzKS/3+wgAAADaRocszKeeeionnHBCJk+enMsuuyxNTU2ZPHlyXnvttdKaadOmZcGC\nBbngggty5ZVXZsOGDbn66qtL55ubm/O9730vzc3NmTx5cr7yla/k3nvvzc0339welwQAAEAn1SHD\n++KLL87YsWMzaNCgDBkyJOedd17WrVuXZcuWJUkaGhrym9/8JmeddVZGjhyZ/fbbL+edd16efvrp\nLF26NEny+OOPZ82aNfna176WIUOGZPTo0Tn99NPz7//+72lqamrPywMAAKAT6ZDh/ecaGhqSJD17\n9kySLFu2LE1NTTn44INLawYMGJC+fftm8eLFSZIlS5ZkyJAhqampKa059NBD09DQkFWrVr2L0wMA\nANCZdfjwbmlpybRp03LggQdm0KBBSZK6urpUVFSkurq61dpevXqlrq6utOa/v987SWpra0vnAAAA\noC10+PC+4YYbsnr16nz9619/27UtLS3b9ZxlZWXvdCwAAABI0kE/1fx1U6ZMyYIFC/Kd73wnvXv3\nLh2vra1NY2NjGhoaWt31rq+vL93Vrq2tzTPPPNPq+V6/0/3nd8K3R01NzXaHPR1Lw8aX2nsEClTe\npUt6965t7zGgTdivOjf7FZ2Fvapz2532qh25Ydthw3vKlCmZP39+rrjiivTt27fVuaFDh6ZLly55\n4okncuSRRyZJ1qxZk3Xr1mX48OFJkuHDh2fmzJmpr68vvc/7D3/4Q6qrq0svWd8R9fX12bp16zu8\nKnZFlT5sr1NrbmrK+vXr23sMaBP2q87NfkVnYa/q3HanvaqysjL9+vXbrrUdMrxvuOGG/O53v8vf\n/M3fpFu3bqU71dXV1enatWuqq6tz7LHH5mc/+1l69OiR7t2758Ybb8yIESNywAEHJEkOOeSQDBo0\nKNdcc03OOOOMbNiwIdOnT8/xxx+fiooO+WMBAABgF9QhC/POO+9MklxxxRWtjp933nkZN25ckuSs\ns85KeXl5fvCDH2Tr1q0ZPXp0vvCFL5TWlpeX58ILL8wNN9yQv/3bv01VVVXGjRuXCRMmvGvXAQAA\nQOfXIcN7+vTpb7umsrIyEydOzMSJE990Td++fXPRRRe15WgAAADQSof/VHMAAADYlQlvAAAAKJDw\nBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIAC\nCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAA\nKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYA\nAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglv\nAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ\n8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACA\nAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAA\nACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKFBFew/Q3ubMmZNf//rXqaury7777puzzz47Bxxw\nQHuPBQAAQCexW9/xnjdvXv7v//2/mTBhQr7//e9nn332yeTJk1NfX9/eowEAANBJ7Nbhfccdd+S4\n447LuHHjMnDgwEyaNCndunXLb37zm/YeDQAAgE5itw3vxsbGLFu2LKNGjSodKysry6hRo7J48eJ2\nnAwAAIDOZLcN75dffjnNzc3p1atXq+O9evVKXV1dO00FAABAZ7Pbf7jaGykrK9vhx1RU+FF2VhVV\n3VO5/4j2HuNd071bZUb079neY7xrunetTGXljv9vHnZF9qvOzX5FZ2Gv6tx2p71qRxqwrKWlpaXA\nWXZZjY2NOfPMM3PBBRfk8MMPLx2/9tpr09DQkL/+679ux+kAAADoLHbbl5pXVFRk6NChWbhwYelY\nS0tLnnjiiYwYsfv8Bg7+3LRp09p7BIDtYr8COgJ7Fclu/lLzk046Kddee22GDh2aAw44IHfccUde\nffXVjB8/vr1Hg3bz/PPPt/cIANvFfgV0BPYqkt08vD/wgQ/k5Zdfzs0335y6urrsu+++ufTSS1NT\nU9PeowEAANBJ7NbhnSTHH398jj/++PYeAwAAgE5qt32PNwAAALwbhDfQytFHH93eIwBsF/sV0BHY\nq0h24z8nBgAAAO8Gd7wBAACgQMIbAAAACiS8AQAAoEDCG3ZTp59+eubPn9/eYwC8JXsV0FHYr3gr\nwht4xxYtWpTTTz89DQ0N27V++vTp+dKXvpTPfvazueqqq7J27dqCJwTYsb3qoYceyuTJk/OFL3wh\np59+ep599tl3YUKAP9ne/aqpqSk///nP861vfStnnnlmvvSlL+Waa67Jhg0b3qVJ2V7CG3jHduSP\nI8yaNStz5szJpEmT8t3vfjfdunXL5MmT09jYWOCEADu2V23ZsiUHHnhgzjjjjAInAnhj27tfvfrq\nq3n22WfzqU99Kt///vfz13/91/nP//zPfP/73y94QnZURXsPALy5lpaW/OpXv8rdd9+dl156KbW1\ntTnuuOPyiU98IitXrsy0adOyePHidOvWLWPGjMnnPve5VFVVlR5/zz335I477sjatWvTs2fPjBkz\nJhMnTtzm+yxatChXXnllbrzxxlRXVydJVqxYkQsvvDDXXntt+vbtm3Xr1mXKlCl56qmn0tjYmP79\n++fMM8/MwIED853vfCdJcvbZZydJxo0bl/POO+8Nr2n27Nk59dRTc/jhhydJvvrVr2bSpEl56KGH\n8oEPfKBNf37Au6Mz7lVjx45Nkrz44ott+rMC2ldn26+qq6tz6aWXtjo2ceLEXHLJJXnppZfSp0+f\nNvvZ8c4Ib9iF3XTTTfnNb36Ts846KwceeGA2bNiQ5557Lq+99lq++93vZvjw4fm7v/u7bNy4Mf/8\nz/+cqVOnljbl//iP/8i//Mu/5LOf/WxGjx6dhoaGPPXUUzs9yw033JCmpqZcddVV6dq1a1avXp2q\nqqr07ds3F1xwQa6++ur86Ec/Svfu3dO1a9c3fI4XXnghdXV1GTVqVOlYdXV1hg0blsWLFwtv6KA6\n214FdF67w361adOmlJWVpUePHjs9G21PeMMuasuWLZk9e3bOOeec0p2X/v37Z8SIEbnrrruydevW\nfPWrX03Xrl0zaNCgTJw4MX//93+fz372s6mpqcmMGTPysY99LB/5yEdKzzl06NCdnuell17KmDFj\nMmjQoNIsr+vZs2eSpKampvRb3TdSV1eXJOnVq1er47169SqdAzqWzrhXAZ3T7rBfbd26Nf/6r/+a\nY445ptWdetqf8IZd1OrVq9PY2JiDDz54m3Nr1qzJPvvs0+q3nyNGjEhLS0vWrFmTJNmwYcMbPnZn\nnXDCCbn++uvz+OOPZ9SoUXn/+9+fIUOGvOn6+++/Pz/96U+TJGVlZbn44otTXv7GHyvR0tLypueA\nXVtn3KsOPPDANpsH2HV09v2qqakpP/jBD1JWVpZzzjmnzeakbQhv2EW91UuKWlpaUlZWtlOPfSNv\n9FxNTU2tvj722GMzevToPProo3n88ccza9asfO5zn2v1W9//7vDDD8+wYcNKX/fu3bv0CZsbN25M\nbW1t6Vx9fX323XffHZoZ2DV0xr0K6Jw68371enS/9NJLufzyy93t3gW5xQS7qPe85z3p2rVrFi5c\nuM25QYMGZcWKFXnttddKx5566qmUl5dnwIABqaqqSr9+/d7wsW+kpqYmSVr96Ynly5dvs6537945\n7rjjcsEFF+Tkk0/O3XffnSSpqPjT7/Cam5tLa6uqqrLXXnuV/lVWVqZ///6pra1tNVdDQ0OWLFmS\nESNGbNeswK6lM+5VQOfUWfer16P7hRdeyOWXX156mTq7FuENu6jKysqccsopuemmm3Lffffl+eef\nz5IlS3LPPffkgx/8YCoqKnLNNddk1apVeeKJJ3LjjTdm7NixpY3+tNNOy+23357Zs2dn7dq1WbZs\nWebMmfOG32vvvfdOnz59csstt2Tt2rV59NFHc8cdd7RaM23atDz++ON54YUXsmzZsjz55JOl9yT1\n7ds3ZWVleeSRR1JfX58tW7a86XWdeOKJmTFjRubPn5+VK1fmmmuuSZ8+fXLEEUe00U8OeDd11r3q\nlVdeyYoVK7Jq1aokyXPPPZcVK1b4PArowDrjftXc3Jyrr746y5cvz9e+9rU0Njamrq4udXV1/lTr\nLqbLFVdccUV7DwG8sZEjR6a5uTm33357fvnLX+axxx7LoEGDctBBB2X06NF5+OGHc/PNN+fhhx/O\nYYcdls9//vOl35Duu+++qampyZw5czJz5szMnz8/tbW1GT16dJLk1ltvzdFHH50BAwakvLw8w4YN\ny7333puZM2fmxRdfzCc+8Yn8/ve/z0knnZTq6uo8+uijmTNnTmbNmpUHHnggw4cPz9lnn52uON2a\nQgAACeVJREFUXbume/fuKS8vz6xZs3Lrrbdm/fr1bxrSBx54YF599dXceuutmTNnTnr37p2vf/3r\npf9TAzqezrhXzZs3L9/73vfyu9/9Lkny4IMP5q677kr37t0zcuTId+cHC7S5zrZfvf4nyTZv3pw7\n77wzt99+e+nfqFGj0q9fv3f158ubK2vZ3r/ODgAAAOwwLzUHAACAAglvAAAAKJDwBgAAgAIJbwAA\nACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwDgTV1xxRW58sor23sMAOjQKtp7\nAABgW88//3x++ctfZuHChVm/fn0qKioyZMiQHHXUUTnuuOPStWvXd2WOsrKyQp9/5syZGTRoUI44\n4ohCvw8AtCfhDQC7mEcffTQ//OEPU1lZmbFjx2bIkCFpbGzMU089lZtuuimrV6/OF7/4xfYes03M\nnDkz73//+4U3AJ2a8AaAXcgLL7yQH/3oR+nfv38uv/zy9OrVq3Tuwx/+cJ5//vk8+uij7Tjhrm/r\n1q2pqKgo/G49AGwv4Q0Au5Bf/vKX2bJlS84999xW0f26vfbaKyeccEKSpLm5OTNmzMjcuXOzfv36\n1NbW5oMf/GA+9alPpaJi+/4v/r777sucOXOyatWq0svZTz311BxyyCFvuP7ee+/NT37yk1x77bXp\n27dv6fiiRYty5ZVX5tvf/nZGjhyZJFm7dm1+/vOfZ/Hixdm0aVNqamoyYsSIfOlLX0r37t1z+umn\nJ0nmzp2buXPnJknGjRuX8847L0myfv36/OIXv8iCBQvS0NCQvffeOyeddFKOPfbYbb7v17/+9axc\nuTJz587Nhg0bMnXq1HTr1i0zZszI/fffn3Xr1qWqqioDBw7MaaedllGjRm3XzwcA2oLwBoBdyKOP\nPpq99torw4YNe9u1P/nJT3LfffflqKOOykc/+tEsXbo0M2fOzOrVq/Otb33rbR9/yy235NZbb82I\nESNy+umnp6KiIkuWLMkTTzzxpuG9vRobG/O//tf/SlNTU0444YTU1tZm/fr1efTRR7Np06Z07949\nX/va1/KTn/wkw4YNy3HHHZfkT79YSJKNGzfm0ksvTXl5eU444YTU1NRkwYIFue6667Jly5aceOKJ\nrb7fbbfdloqKinz0ox9NY2NjKioqcvPNN2fWrFk57rjjsv/++2fz5s155plnsnz5cuENwLtKeAPA\nLmLz5s1Zv379dr3f+dlnn819992XD33oQ6X3e3/4wx9OTU1Nfv3rX2fRokWlO89vZO3atbntttsy\nZsyY/M//+T9Lxz/ykY+88wtJsnr16rz44ou54IILcuSRR5aOn3rqqaX/PuaYY/LTn/40/fv3zzHH\nHNPq8f/2b/+WlpaWfP/730+PHj2SJMcdd1x+9KMf5ZZbbsn/+B//I5WVlaX1W7duzd///d+3utO/\nYMGCvO9978ukSZPa5JoAYGf5c2IAsIvYvHlzkqSqqupt1y5YsCBJcvLJJ7c6/vrXb/c+8Iceeigt\nLS351Kc+tTOjvq3q6uokyWOPPZbXXntthx//4IMP5rDDDktzc3Nefvnl0r9DDz00DQ0NWb58eav1\n48eP3+bl9T169Mjq1auzdu3anb8QAGgD7ngDwC6ie/fuSZItW7a87doXX3wx5eXl2XvvvVsdr62t\nTXV1dV588cUkSUNDQ6vwraioSM+ePfPCCy+kvLw8AwcObMMr+C/9+/fPySefnNtvvz2//e1vc+CB\nB+bwww/PBz/4wVKUv5n6+vo0NDTkrrvuyl133fWGazZu3Njq6379+m2zZsKECfnf//t/5+tf/3oG\nDx6c0aNHlz4lHgDeTcIbAHYR3bt3z5577pmVK1e+7dqWlpbtes5p06aVPrgsSUaOHJlvf/vb2/34\nP/dmnxTe3Ny8zbEzzzwz48ePz8MPP5w//OEPufHGGzNr1qxMnjw5vXv3ftPv8fpzffCDH8z48ePf\ncM2fx/Mb/V3z9773vfmnf/qn0ve/5557cscdd2TSpEmtPqANAIomvAFgF/K+970vd999d5YsWfKW\nH7DWv3//NDc3Z+3atRkwYEDp+MaNG9PQ0FC6A3zKKadk7NixpfOvv1967733TnNzc1avXp199tln\nu+d7/fGbNm1q9anmL7zwwhuuHzx4cAYPHpxPfvKTWbx4cS677LLceeedpU80f6OQr6mpSVVVVZqb\nm3PwwQdv92xvNu/48eMzfvz4vPrqq7n88stzyy23CG8A3lXe4w0Au5BTTjkl3bp1yz//8z9v83Lq\n5E8fivb//t//y1/8xV8kSe64445W53/9618n+VPAJ8nAgQNz8MEHl/7tt99+SZIjjjgiZWVlufXW\nW3fo7vfrL23/4x//WDrW3Nycu+++u9W6zZs3b3MXfPDgwSkrK8vWrVtLx7p165aGhoZW68rLyzNm\nzJg8+OCDWbVq1TYz1NfXb9esr7zySquvu3Xrlr333juNjY3b9XgAaCvueAPALmSvvfbK+eefnx/9\n6Ef55je/WXpPcmNjY55++uk88MAD+cu//MuceOKJGTduXO66665s2rQpI0eOzJIlS3LfffflyCOP\nfMtPNE/+FNCf/OQnc9ttt+Xyyy/PmDFjUlFRkWeeeSa9e/fOpz/96Td83KBBgzJ8+PDcdNNNefnl\nl9OzZ8/Mmzdvm8h+4oknMnXq1Lz//e/Pe97znjQ3N2fu3Lnp0qVL3v/+95fWDR06NAsXLsztt9+e\n3r17p3///jnggANyxhlnZNGiRbnkkkvyoQ99KIMGDcorr7ySZcuW5cknn8yUKVPe9mf5zW9+Mwcd\ndFCGDh2anj17ZunSpXnggQdKfwcdAN4tXa644oor2nsIAOC/DBgwIB/4wAeyadOmPPbYY5k3b14W\nLVqUrl275qMf/Wg+8YlPpLy8PIcddli6dOmSBQsW5IEHHsjLL7+c448/PhMnTkx5+du/qO2ggw5K\nv379snjx4sybNy9PP/10KisrM378+PTv3z9JMnfu3JSVlWXcuHGlxx188MFZuXJl7r///ixbtixj\nxozJhz70odx3330ZP358+vXrl8rKymzYsCELFy7Mgw8+mKeffjr9+vXLF7/4xRx44IGl5xo6dGiW\nL1+e3/72t5k3b16amppyxBFHpKqqKsccc0w2b96c+fPn54EHHsjKlStTXV2dk046qXTn/sUXX8zc\nuXNz1FFHZdCgQa2ur6mpKUuXLs38+fPzyCOPZPPmzTn55JMzYcKEN32vOgAUoaxlZz9dBQAAAHhb\n3uMNAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAA\nAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABfr/oQUa20GZR0gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10abdf490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ** Plot top terms for each cluster and the cluster sizes **\n",
    "n_terms = input_with_default_int('Number of top terms', 10)\n",
    "\n",
    "# --> top terms\n",
    "plot_cluster_top_terms(doc_term_data['doc_term_matrix'], doc_term_data['term_labels'], n_terms, best_coclustMod_model)\n",
    "# --> cluster sizes\n",
    "plot_cluster_sizes(best_coclustMod_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of cluster: [default: 1] \n",
      "Number of top terms: [default: 25] \n",
      "Number of neighbors: [default: 10] \n"
     ]
    }
   ],
   "source": [
    "# ** Plot the term graph for a given cluster of terms **\n",
    "n_cluster = input_with_default_int('Number of cluster', 1)\n",
    "n_top_terms = input_with_default_int('Number of top terms', 25)\n",
    "n_neighbors = input_with_default_int('Number of neighbors', 10)\n",
    "\n",
    "graph = get_term_graph(X = doc_term_data['doc_term_matrix'], model = best_coclustMod_model, \n",
    "                       terms = doc_term_data['term_labels'], n_cluster = n_cluster, \n",
    "                       n_top_terms = n_top_terms, n_neighbors = n_neighbors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "require.config({\n",
       "  paths: {\n",
       "      d3: '//cdnjs.cloudflare.com/ajax/libs/d3/3.4.8/d3.min'\n",
       "  }\n",
       "});"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "require.config({\n",
    "  paths: {\n",
    "      d3: '//cdnjs.cloudflare.com/ajax/libs/d3/3.4.8/d3.min'\n",
    "  }\n",
    "});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "           window.graph={'nodes': [{'group': 0, 'name': u'patients           '}, {'group': 0, 'name': u'cells              '}, {'group': 0, 'name': u'cases              '}, {'group': 0, 'name': u'normal             '}, {'group': 0, 'name': u'growth             '}, {'group': 0, 'name': u'blood              '}, {'group': 0, 'name': u'treatment          '}, {'group': 0, 'name': u'cell               '}, {'group': 0, 'name': u'children           '}, {'group': 0, 'name': u'hormone            '}, {'group': 0, 'name': u'increased          '}, {'group': 0, 'name': u'dna                '}, {'group': 0, 'name': u'human              '}, {'group': 0, 'name': u'rats               '}, {'group': 0, 'name': u'disease            '}, {'group': 0, 'name': u'cancer             '}, {'group': 0, 'name': u'group              '}, {'group': 0, 'name': u'tissue             '}, {'group': 0, 'name': u'acid               '}, {'group': 0, 'name': u'liver              '}, {'group': 0, 'name': u'plasma             '}, {'group': 0, 'name': u'studies            '}, {'group': 0, 'name': u'renal              '}, {'group': 0, 'name': u'activity           '}, {'group': 0, 'name': u'increase           '}, {'group': 1, 'name': u'thyroid            '}, {'group': 1, 'name': u'hr                 '}, {'group': 1, 'name': u'ca                 '}, {'group': 1, 'name': u'weight             '}, {'group': 1, 'name': u'genetic            '}, {'group': 1, 'name': u'ml                 '}, {'group': 1, 'name': u'unilateral         '}, {'group': 1, 'name': u'transforming       '}, {'group': 1, 'name': u'hepatic            '}, {'group': 1, 'name': u'hgh                '}, {'group': 1, 'name': u'chronic            '}, {'group': 1, 'name': u'considerable       '}, {'group': 1, 'name': u'administration     '}, {'group': 1, 'name': u'schizophrenic      '}, {'group': 1, 'name': u'matched            '}, {'group': 1, 'name': u'characteristic     '}, {'group': 1, 'name': u'arterial           '}, {'group': 1, 'name': u'calcium            '}, {'group': 1, 'name': u'ffa                '}, {'group': 1, 'name': u'bone               '}, {'group': 1, 'name': u'eeg                '}, {'group': 1, 'name': u'nucleic            '}, {'group': 1, 'name': u'vitamin            '}, {'group': 1, 'name': u'day                '}, {'group': 1, 'name': u'failure            '}, {'group': 1, 'name': u'rat                '}, {'group': 1, 'name': u'diffuse            '}, {'group': 1, 'name': u'lymphocytes        '}, {'group': 1, 'name': u'died               '}, {'group': 1, 'name': u'promoting          '}, {'group': 1, 'name': u'thymidine          '}, {'group': 1, 'name': u'release            '}, {'group': 1, 'name': u'control            '}, {'group': 1, 'name': u'hela               '}, {'group': 1, 'name': u'fine               '}, {'group': 1, 'name': u'bile               '}, {'group': 1, 'name': u'parathyroid        '}, {'group': 1, 'name': u'decreased          '}, {'group': 1, 'name': u'content            '}, {'group': 1, 'name': u'rise               '}, {'group': 1, 'name': u'diagnosed          '}, {'group': 1, 'name': u'therapeutic        '}, {'group': 1, 'name': u'patient            '}, {'group': 1, 'name': u'therapy            '}, {'group': 1, 'name': u'type               '}, {'group': 1, 'name': u'persons            '}, {'group': 1, 'name': u'animals            '}, {'group': 1, 'name': u'normals            '}, {'group': 1, 'name': u'tissues            '}, {'group': 1, 'name': u'cytoplasm          '}, {'group': 1, 'name': u'soft               '}, {'group': 1, 'name': u'lymphocyte         '}, {'group': 1, 'name': u'hamster            '}, {'group': 1, 'name': u'hypertrophy        '}, {'group': 1, 'name': u'agar               '}, {'group': 1, 'name': u'concentrations     '}, {'group': 1, 'name': u'disturbed          '}, {'group': 1, 'name': u'cancers            '}, {'group': 1, 'name': u'weights            '}, {'group': 1, 'name': u'days               '}, {'group': 1, 'name': u'fresh              '}, {'group': 1, 'name': u'child              '}, {'group': 1, 'name': u'phage              '}, {'group': 1, 'name': u'retardation        '}, {'group': 1, 'name': u'erythrocytes       '}, {'group': 1, 'name': u'significantly      '}, {'group': 1, 'name': u'observations       '}, {'group': 1, 'name': u'postmenopausal     '}, {'group': 1, 'name': u'proliferative      '}, {'group': 1, 'name': u'hypopituitary      '}, {'group': 1, 'name': u'amino              '}, {'group': 1, 'name': u'secretion          '}, {'group': 1, 'name': u'elevation          '}, {'group': 1, 'name': u'incorporated       '}, {'group': 1, 'name': u'occurred           '}, {'group': 1, 'name': u'diagnostic         '}, {'group': 1, 'name': u'total              '}, {'group': 1, 'name': u'dioxide            '}, {'group': 1, 'name': u'observed           '}, {'group': 1, 'name': u'ventilation        '}, {'group': 1, 'name': u'excreted           '}, {'group': 1, 'name': u'syndrome           '}, {'group': 1, 'name': u'diabetic           '}, {'group': 1, 'name': u'dividing           '}, {'group': 1, 'name': u'elevated           '}, {'group': 1, 'name': u'giant              '}, {'group': 1, 'name': u'zones              '}, {'group': 1, 'name': u'compensatory       '}, {'group': 1, 'name': u'bands              '}, {'group': 1, 'name': u'lymphoid           '}, {'group': 1, 'name': u'phosphate          '}, {'group': 1, 'name': u'lines              '}, {'group': 1, 'name': u'detected           '}, {'group': 1, 'name': u'neoplastic         '}, {'group': 1, 'name': u'competent          '}, {'group': 1, 'name': u'statistically      '}, {'group': 1, 'name': u'fatty              '}, {'group': 1, 'name': u'secretory          '}, {'group': 1, 'name': u'diagnosis          '}, {'group': 1, 'name': u'pituitary          '}, {'group': 1, 'name': u'hepatitis          '}, {'group': 1, 'name': u'autistic           '}, {'group': 1, 'name': u'sinus              '}, {'group': 1, 'name': u'irregular          '}, {'group': 1, 'name': u'delay              '}, {'group': 1, 'name': u'dwarfism           '}, {'group': 1, 'name': u'deposits           '}, {'group': 1, 'name': u'synthesis          '}, {'group': 1, 'name': u'difference         '}, {'group': 1, 'name': u'start              '}, {'group': 1, 'name': u'increases          '}, {'group': 1, 'name': u'deficiency         '}, {'group': 1, 'name': u'dehydrogenase      '}, {'group': 1, 'name': u'ducts              '}, {'group': 1, 'name': u'schizophrenia      '}, {'group': 1, 'name': u'similar            '}, {'group': 1, 'name': u'living             '}, {'group': 1, 'name': u'nephrectomy        '}, {'group': 1, 'name': u'advanced           '}, {'group': 1, 'name': u'cytoplasmic        '}, {'group': 1, 'name': u'chemotherapy       '}, {'group': 1, 'name': u'degree             '}, {'group': 1, 'name': u'metastatic         '}, {'group': 1, 'name': u'decrease           '}, {'group': 1, 'name': u'showed             '}, {'group': 1, 'name': u'designated         '}, {'group': 1, 'name': u'clinical           '}, {'group': 1, 'name': u'change             '}, {'group': 1, 'name': u'carefully          '}, {'group': 1, 'name': u'enzyme             '}, {'group': 1, 'name': u'stimulated         '}, {'group': 1, 'name': u'granules           '}, {'group': 1, 'name': u'carbon             '}, {'group': 1, 'name': u'severity           '}, {'group': 1, 'name': u'dry                '}, {'group': 1, 'name': u'necrosis           '}, {'group': 1, 'name': u'slight             '}, {'group': 1, 'name': u'rabbit             '}, {'group': 1, 'name': u'subtilis           '}, {'group': 1, 'name': u'histological       '}, {'group': 1, 'name': u'biopsy             '}, {'group': 1, 'name': u'controls           '}, {'group': 1, 'name': u'antigens           '}, {'group': 1, 'name': u'scores             '}, {'group': 1, 'name': u'blocks             '}, {'group': 1, 'name': u'subjects           '}, {'group': 1, 'name': u'extracts           '}, {'group': 1, 'name': u'marrow             '}, {'group': 1, 'name': u'culture            '}, {'group': 1, 'name': u'levels             '}, {'group': 1, 'name': u'metabolism         '}, {'group': 1, 'name': u'ventricular        '}, {'group': 1, 'name': u'thymus             '}, {'group': 1, 'name': u'monkey             '}, {'group': 1, 'name': u'kidney             '}, {'group': 1, 'name': u'hyperplasia        '}, {'group': 1, 'name': u'venous             '}, {'group': 1, 'name': u'bacillus           '}, {'group': 1, 'name': u'defective          '}, {'group': 1, 'name': u'breast             '}, {'group': 1, 'name': u'significant        '}, {'group': 1, 'name': u'groups             '}, {'group': 1, 'name': u'inactivation       '}], 'links': [{'source': 0, 'target': 15, 'value': 0.39737733582527129}, {'source': 0, 'target': 25, 'value': 0.38088163250809404}, {'source': 0, 'target': 26, 'value': 0.31862125469229569}, {'source': 0, 'target': 6, 'value': 0.29837515410740212}, {'source': 0, 'target': 27, 'value': 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0.21720839573894737}, {'source': 23, 'target': 185, 'value': 0.20919054414739632}, {'source': 23, 'target': 1, 'value': 0.20846949040292109}, {'source': 23, 'target': 185, 'value': 0.20483662259967564}, {'source': 24, 'target': 185, 'value': 0.42543955853552573}, {'source': 24, 'target': 185, 'value': 0.42045004777954809}, {'source': 24, 'target': 185, 'value': 0.37818779029489091}, {'source': 24, 'target': 186, 'value': 0.36867336089166824}, {'source': 24, 'target': 186, 'value': 0.34619785068449427}, {'source': 24, 'target': 186, 'value': 0.32756089104020925}, {'source': 24, 'target': 186, 'value': 0.32338083338177726}, {'source': 24, 'target': 187, 'value': 0.30541728051692274}]};\n",
       "           "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Javascript\n",
    "#runs arbitrary javascript, client-side\n",
    "Javascript(\"\"\"\n",
    "           window.graph={};\n",
    "           \"\"\".format(graph))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "require(['d3'], function(d3){\n",
       "  //a weird idempotency thing\n",
       "  $(\"#chart1\").remove();\n",
       "  //create canvas\n",
       "  element.append(\"<div id='chart1'></div>\");\n",
       "  $(\"#chart1\").width(\"1160px\");\n",
       "  $(\"#chart1\").height(\"800px\");        \n",
       "  var margin = {top: 20, right: 20, bottom: 30, left: 40};\n",
       "  var width = 1280 - margin.left - margin.right;\n",
       "  var height = 800 - margin.top - margin.bottom;\n",
       "  var svg = d3.select(\"#chart1\").append(\"svg\")\n",
       "    .style(\"position\", \"relative\")\n",
       "    .style(\"max-width\", \"960px\")\n",
       "    .attr(\"width\", width + \"px\")\n",
       "    .attr(\"height\", (height + 50) + \"px\")\n",
       "    .call(d3.behavior.zoom().on(\"zoom\", redraw))\n",
       "    .append(\"g\")\n",
       "    .attr(\"transform\", \"translate(\" + margin.left + \",\" + margin.top + \")\");\n",
       "    \n",
       "    \n",
       "  function redraw() {\n",
       "      svg.attr(\"transform\",\n",
       "               \"translate(\" + d3.event.translate + \")\"\n",
       "               + \" scale(\" + d3.event.scale + \")\");\n",
       "  }   \n",
       "\n",
       "  var color = d3.scale.category20();\n",
       "\n",
       "  var force = d3.layout.force()\n",
       "    .charge(-500)\n",
       "    //.linkDistance(5)\n",
       "    .linkDistance(function(d) { return (1 - d.value); })\n",
       "    .size([width, height]);\n",
       "\n",
       "  var graph = window.graph;\n",
       "    \n",
       "  force\n",
       "      .nodes(graph.nodes)\n",
       "      .links(graph.links)\n",
       "      .start();\n",
       "\n",
       "  var link = svg.selectAll(\".link\")\n",
       "      .data(graph.links)\n",
       "      .enter().append(\"line\")\n",
       "      .attr(\"class\", \"link\")\n",
       "      .style(\"stroke\", \"#999;\")\n",
       "      .style(\"stroke-opacity\", .6)\n",
       "      .style(\"stroke-width\", function(d) { return Math.sqrt(d.value); })\n",
       "  \n",
       "      .style(\"stroke\", \"blue\");\n",
       "\n",
       "  var node = svg.selectAll(\".node\")\n",
       "      .data(graph.nodes)\n",
       "      .enter().append(\"g\")\n",
       "      .attr(\"class\", \"node\")\n",
       "      .call(force.drag);\n",
       "    \n",
       "  node.append(\"circle\")\n",
       "      .attr(\"class\", \"node_circle\")\n",
       "      .attr(\"r\", 8)\n",
       "      .style(\"fill\", function(d) { return color(d.group); });\n",
       "\n",
       "  node.append(\"text\")\n",
       "      .attr(\"class\", \"node_text\")\n",
       "      .attr(\"dx\", 12)\n",
       "      .attr(\"dy\", \".35em\")\n",
       "      .text(function(d) { return d.name });\n",
       "\n",
       "  node.append(\"title\")\n",
       "      .text(function(d) { return d.name; });\n",
       "\n",
       "  var node_text = svg.selectAll(\".node_text\");\n",
       "  var node_circle = svg.selectAll(\".node_circle\");\n",
       "    \n",
       "  force.on(\"tick\", function() {\n",
       "    link.attr(\"x1\", function(d) { return d.source.x; })\n",
       "        .attr(\"y1\", function(d) { return d.source.y; })\n",
       "        .attr(\"x2\", function(d) { return d.target.x; })\n",
       "        .attr(\"y2\", function(d) { return d.target.y; });\n",
       "\n",
       "    node_circle.attr(\"cx\", function(d) { return d.x; })\n",
       "        .attr(\"cy\", function(d) { return d.y; });\n",
       "      \n",
       "    node_text.attr(\"x\", function(d) { return d.x; })\n",
       "        .attr(\"y\", function(d) { return d.y; });\n",
       "  });\n",
       "});"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "require(['d3'], function(d3){\n",
    "  //a weird idempotency thing\n",
    "  $(\"#chart1\").remove();\n",
    "  //create canvas\n",
    "  element.append(\"<div id='chart1'></div>\");\n",
    "  $(\"#chart1\").width(\"1160px\");\n",
    "  $(\"#chart1\").height(\"800px\");        \n",
    "  var margin = {top: 20, right: 20, bottom: 30, left: 40};\n",
    "  var width = 1280 - margin.left - margin.right;\n",
    "  var height = 800 - margin.top - margin.bottom;\n",
    "  var svg = d3.select(\"#chart1\").append(\"svg\")\n",
    "    .style(\"position\", \"relative\")\n",
    "    .style(\"max-width\", \"960px\")\n",
    "    .attr(\"width\", width + \"px\")\n",
    "    .attr(\"height\", (height + 50) + \"px\")\n",
    "    .call(d3.behavior.zoom().on(\"zoom\", redraw))\n",
    "    .append(\"g\")\n",
    "    .attr(\"transform\", \"translate(\" + margin.left + \",\" + margin.top + \")\");\n",
    "    \n",
    "    \n",
    "  function redraw() {\n",
    "      svg.attr(\"transform\",\n",
    "               \"translate(\" + d3.event.translate + \")\"\n",
    "               + \" scale(\" + d3.event.scale + \")\");\n",
    "  }   \n",
    "\n",
    "  var color = d3.scale.category20();\n",
    "\n",
    "  var force = d3.layout.force()\n",
    "    .charge(-500)\n",
    "    //.linkDistance(5)\n",
    "    .linkDistance(function(d) { return (1 - d.value); })\n",
    "    .size([width, height]);\n",
    "\n",
    "  var graph = window.graph;\n",
    "    \n",
    "  force\n",
    "      .nodes(graph.nodes)\n",
    "      .links(graph.links)\n",
    "      .start();\n",
    "\n",
    "  var link = svg.selectAll(\".link\")\n",
    "      .data(graph.links)\n",
    "      .enter().append(\"line\")\n",
    "      .attr(\"class\", \"link\")\n",
    "      .style(\"stroke\", \"#999;\")\n",
    "      .style(\"stroke-opacity\", .6)\n",
    "      .style(\"stroke-width\", function(d) { return Math.sqrt(d.value); })\n",
    "  \n",
    "      .style(\"stroke\", \"blue\");\n",
    "\n",
    "  var node = svg.selectAll(\".node\")\n",
    "      .data(graph.nodes)\n",
    "      .enter().append(\"g\")\n",
    "      .attr(\"class\", \"node\")\n",
    "      .call(force.drag);\n",
    "    \n",
    "  node.append(\"circle\")\n",
    "      .attr(\"class\", \"node_circle\")\n",
    "      .attr(\"r\", 8)\n",
    "      .style(\"fill\", function(d) { return color(d.group); });\n",
    "\n",
    "  node.append(\"text\")\n",
    "      .attr(\"class\", \"node_text\")\n",
    "      .attr(\"dx\", 12)\n",
    "      .attr(\"dy\", \".35em\")\n",
    "      .text(function(d) { return d.name });\n",
    "\n",
    "  node.append(\"title\")\n",
    "      .text(function(d) { return d.name; });\n",
    "\n",
    "  var node_text = svg.selectAll(\".node_text\");\n",
    "  var node_circle = svg.selectAll(\".node_circle\");\n",
    "    \n",
    "  force.on(\"tick\", function() {\n",
    "    link.attr(\"x1\", function(d) { return d.source.x; })\n",
    "        .attr(\"y1\", function(d) { return d.source.y; })\n",
    "        .attr(\"x2\", function(d) { return d.target.x; })\n",
    "        .attr(\"y2\", function(d) { return d.target.y; });\n",
    "\n",
    "    node_circle.attr(\"cx\", function(d) { return d.x; })\n",
    "        .attr(\"cy\", function(d) { return d.y; });\n",
    "      \n",
    "    node_text.attr(\"x\", function(d) { return d.x; })\n",
    "        .attr(\"y\", function(d) { return d.y; });\n",
    "  });\n",
    "});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# ** Compute spectral co-clustering with the CoclustSpecMod approach **\n",
    "\n",
    "n_clusters = best_coclustMod_model.n_clusters\n",
    "# Perform co-clustering\n",
    "coclust_specMod_model = CoclustSpecMod(n_clusters=n_clusters, random_state=0)\n",
    "coclust_specMod_model.fit(doc_term_data['doc_term_matrix'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of top terms: [default: 10] \n"
     ]
    },
    {
     "data": {
      "image/png": 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o3Lix49jSpUvZs2cPt956a4na++qrr9iwYcMZr/3kk0/44YcfnP7FxcURERFBTEyM47o7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\n80/7qd/nq5KTk9m2bRseHh5ERUXRpEkTxzq35WxItTd58mRj4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f9xW4qLizl37tw1BUat\nWrUwm80kJiZisViuu/9jjz3GY489Rn5+PnPmzGH16tVlij4RkVulYVEiItVcQEAAISEhbN26FcMw\nOHDgQJkhOT/Xxx9/zPnz57l06RIrV650TJZu06YNeXl5bNiwgeLiYux2OxkZGRw6dKjcx37wwQc5\ndOgQu3fvxm63s3PnTlJTU8tMyL6ZX/ziF4422O12Dh8+zPbt23nooYcA6NGjB59++imHDh3CMAzy\n8/M5ceLET667++672bdvH7m5udhsNlavXv2Tbenduzcff/yxY6jT5cuX2b9/f7nmcQQGBtKuXTsS\nExPJzc3FMAxOnDjBxYsXCQoKol27dsyfP58LFy4AV4rG5ORkAA4cOMCJEyew2+14eXlhsVjw8PAo\nV34iIjeingsRkWrgx9+W/9gLL7zAvHnzWLNmDW3atKFjx46UlJTc1jk7d+7MtGnTHHeLujrZ28fH\nh5dffpn333+f1atXU1xcTJ06dfiv//qvch+7Tp06TJgwgaSkJN555x1q167NxIkTrxnqdCM1atRg\n8uTJLF68mOXLlxMcHMyIESMcd2hq164dNpuNBQsWkJOTg7+/P7GxsURERNx0XefOnTl06BBjx46l\nZs2aDBgwgB07dty0LW3atKGoqIi//OUvZGVlYbFYaNy4McOHDy/Xtbz44ossW7aM//mf/6GwsJB6\n9eoxYcIEAOLi4li5ciUvvfQSFy9eJDAwkAcffJD27duTl5fHggULOHfuHF5eXrRs2ZInn3yyXOcU\nEbkRk2EYRkU3QkREREREKj8NixIREREREadQcSEiIiIiIk6h4kJERERERJxCxYWIiIiIiDiFigsR\nEREREXEKFRciIiIiIuIUKi5ERERERMQpVFyIiIiIiIhTqLgQERERERGnUHEhIiIiIiJOoeJCRERE\nRESc4v8BS9VlUhdJLZIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a803810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qpT59+lxSv2zZMiUmJl52F9tkMumWW26RJK1cuVIxMTEKCAgo+8YBAACAMkDw\nBlAmrFarDh065HiieWZmpnbv3i1/f381bNhQ/v7+TvVeXl6qV6+eGjdu7DT+9ddf68iRI6UG8pyc\nHK1Zs0Zt27bVuXPnlJqaqo8++kjvv/++cQsDAAAAbhLBG0CZSEtLU2Jiokwmk0wmkyZNmiRJSkxM\n1LRp0y6pN5lMpZ4nNTVVsbGxCg8PL3V+2bJleumll2S32xUTE6MVK1Y4PucbAAAAcEcEbwBlom3b\ntsrKyrrm+o0bN5Y6PmPGjMseExAQoFWrVl13bwAAAIAr8XA1AAAAAAAMRPAGAAAAAMBABG8AAAAA\nAAxE8AYAAAAAwEA8XA2Ak2zLGeUV2l3dRrnx8TLL16PqrBcAAADlj+ANwMkv54o0ZMVPrm6j3Mx9\nuJl8PUr/aDMAAACgLHCpOQAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYi\neAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAA\nYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDBtm0aZMGDhyomJgYBQcHa926dU7z06ZNU3x8\nvJo2baqWLVuqb9++2rZtm1PNzp079cgjjygyMlJ33HGH/va3v8lqtTrVfP3113rggQfUrFkzxcTE\naPLkySopKTF8fQAAAACuDcEbMIjValXLli2VnJwsk8l0yXyTJk2UnJysDRs26IMPPlBISIj69eun\nnJwcSdKJEyfUt29fNW7cWKtXr9Z7772nffv26S9/+YvjHHv27NHjjz+uDh06aN26dZo5c6bWrVun\nyZMnl9s6AQAAAFyZp6sbACqrhIQEJSQkSJLsdvsl8w888IDT6wkTJmjx4sXau3ev2rVrp88++0zV\nqlVTcnKyo+bll19Wp06dlJmZqbCwMK1atUqRkZH685//LEkKCwvTuHHjNGzYMI0ePVo+Pj4GrhAA\nAADAtWDHG3ADNptNCxculJ+fnyIjIyVJ58+fl5eXl1Nd9erVJUmbN2921Fwc+3XNuXPntGPHjnLo\nHAAAAMDVELwBF/rss88UERGhxo0ba+7cuVq8eLHq1KkjSWrXrp1OnjypWbNmyWazyWKxaMqUKTKZ\nTPr5558lSffdd5+2bNmiDz/8UCUlJTp+/Lj+/e9/S7pwqToAAAAA1yN4Ay7Url07ffrpp1q1apUS\nEhL05JM80cZhAAAgAElEQVRPOu7xjoiI0PTp0zV79myFh4crJiZGYWFhCgwMlIeHhySpffv2ev75\n5/Xss8/qtttuU3x8vDp27Ci73e6oAQAAAOBaBG/AhWrUqKGwsDDdeeed+uc//ykPDw8tXrzYMf/A\nAw/ohx9+0A8//KBdu3Zp9OjROn36tEJCQhw1Q4cO1Z49e/T9999r586duv/++yVJoaGh5b4eAAAA\nAJfi4WqAG7Hb7Tp//vwl43Xr1pUkLVmyRN7e3mrfvv0lNfXq1ZMkrVy5Ug0bNtQdd9xhbLMAAAAA\nrolbBu+9e/dq1apVSk9Pl8ViUVJSklq3bl1q7ezZs7V+/Xo9/vjj6t69u2P8zJkzSklJ0datW2U2\nmxUXF6eBAwfK29vbUZOZmamUlBQdOHBAfn5+6tq1q3r27Gn4+lA1WK1WHTp0yPFE88zMTO3evVv+\n/v4KCAjQv//9b91///265ZZblJOTo/nz5ys7O1t/+MMfHOd4++231bp1a/n4+Oirr77SSy+9pOef\nf161atVy1MyaNUv33XefzGaz1qxZozfffFOzZs0q9SPMAAAAAJQ/twze586dU6NGjZSQkKCpU6de\ntm7z5s06cOCAAgICLpl77bXXlJeXp/Hjx6uoqEgzZ87U7NmzNXLkSEnS2bNnlZycrKioKA0dOlSH\nDx/Wm2++KV9fX3Xs2NGwtaHqSEtLU2Jiokwmk0wmkyZNmiRJSkxM1JQpU3Tw4EH93//9n3Jzc+Xv\n76/o6Gh98MEHatq0qeMc27Zt09SpU2W1WtWkSRP985//1EMPPeT0dTZs2KDXX39d586dU2RkpObP\nn6/4+PhyXSsAAACAy3PL4B0dHa3o6Ogr1lzcIRw3bpymTJniNHf06FGlpaXp5Zdf1m233SZJGjRo\nkF5++WU99thj8vf319dff63i4mINGzZMHh4eCg4OVkZGhlavXk3wRplo27atsrKyLjs/Z86cq57j\n4hPKr2Tp0qXX1RcAAACA8lUhH65mt9s1Y8YMPfDAAwoODr5kft++ffL19XWEbkmKioqSyWTS/v37\nHTUtWrRwevJzq1atdOzYMVmtVuMXAQAAAACoEipk8P7ggw/k6emprl27ljpvsVjk5+fnNGY2m1Wz\nZk1ZLBZJUl5e3iU1F19frAEAAAAA4GZVuOCdnp6utWvXavjw4dd9rN1u54FTAAAAAIBy5Zb3eF/J\njz/+qPz8fA0bNswxVlJSogULFuijjz7SjBkz5O/vr7y8PKfjSkpKVFBQIH9/f0kXdrd/W3Px9cWa\n61G7dm3H06uBiiznRN7ViyoRs4eHAgKu/3segOt5eXmV+oBVAO7Nmnfa1S3AQFXpZ6vr2dStcMG7\nffv2ioqKchp76aWX1L59eyUkJEiSIiIiVFBQoEOHDjnu8965c6fsdrvCw8MdNampqSopKZHZfGHj\nPy0tTQ0aNJCPj89195Wfny+bzXYzS4Ob8jpbIJ0tcHUb5aakRqCrWyhXJcXFysnJcXUbAG5AQEAA\n379ABeRVXOzqFmCgqvSzlZeXl4KCgq6p1i2Dd2FhobKzsx2vT5w4oYyMDNWsWVOBgYGqWbOmU72H\nh4f8/f1Vv359SVLDhg0VHR2tt956S0OGDFFRUZFSUlLUrl07x272vffeqxUrVmjmzJl68MEHdfjw\nYa1du1aDBg0qv4WiYjhboMJnhri6i/IzfaWrOwAAAAAqFbcM3unp6Zo4caLj9YIFCyRJ8fHxpd7b\nXdoW/8iRIzVv3jy9+OKLMpvNiouLcwrVPj4+GjdunObNm6exY8eqVq1aSkxMVIcOHQxYEQAAAACg\nqnLL4B0ZGanU1NRrrp8xY8YlY76+vho5cuQVjwsNDXUK+AAAAAAAlLUK91RzAAAAAAAqEoI3AAAA\nAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngD\nAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAg\ngjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAA\nAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMA\nAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCC\nNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAA\nBiJ4AwAAAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAA\nAABgIII3AAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3\nAAAAAAAGIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAG\nIngDAAAAAGAggjcAAAAAAAYieAMAAAAAYCCCNwAAAAAABiJ4AwAAAABgIII3AAAAAAAGIngDAAAA\nAGAgT1c3UJq9e/dq1apVSk9Pl8ViUVJSklq3bi1JKi4u1uLFi7V9+3adOHFCPj4+uuOOO9S/f3/V\nqVPHcY4zZ84oJSVFW7duldlsVlxcnAYOHChvb29HTWZmplJSUnTgwAH5+fmpa9eu6tmzZ7mvFwAA\nAABQebnljve5c+fUqFEjDR48uNS5zMxM9erVS6+88oqSkpJ0/PhxvfLKK051r732mo4eParx48dr\n7Nix2rt3r2bPnu2YP3v2rJKTkxUUFKR//OMfGjBggJYtW6b169cbvj4AAAAAQNXhljve0dHRio6O\nLnXOx8dH48aNcxp74okn9Nxzz+n06dOqW7eusrKylJaWppdfflm33XabJGnQoEF6+eWX9dhjj8nf\n319ff/21iouLNWzYMHl4eCg4OFgZGRlavXq1OnbsaPgaAQAAAABVg1vueF+vgoICmUwm+fr6SpL2\n798vX19fR+iWpKioKJlMJu3fv1+StG/fPrVo0UIeHh6OmlatWunYsWOyWq3luwAAAAAAQKVV4YO3\nzWbTokWLdO+99zru37ZYLPLz83OqM5vNqlmzpiwWiyQpLy/vkpqLry/WAAAAAABwsyp08C4uLta0\nadNkMpk0ZMiQq9bb7XaZTKZy6AwAAAAAgAvc8h7va3ExdJ8+fVrjx493elq5v7+/8vLynOpLSkpU\nUFAgf39/SRd2t39bc/H1xZrrUbt2bdnt9us+Du7Pmnfa1S3AQGYPDwUEXP/3PADX8/LyUkBAgKvb\nAHCd+NmqcqtKP1tdz6ZuhQzeF0P3zz//rAkTJqhmzZpO8xERESooKNChQ4cc93nv3LlTdrtd4eHh\njprU1FSVlJTIbL6w8Z+WlqYGDRrIx8fnunvKz8+XzWa7yZXBHXkVF7u6BRiopLhYOTk5rm4DwA0I\nCAjg+xeogPjZqnKrSj9beXl5KSgo6Jpq3fJS88LCQmVkZCgjI0OSdOLECWVkZOjUqVMqKSnR1KlT\ndejQIT399NMqKiqSxWKRxWJRUVGRJKlhw4aKjo7WW2+9pQMHDujHH39USkqK2rVr59jNvvfee+Xp\n6amZM2cqKytL3333ndauXasePXq4atkAAAAAgErILXe809PTNXHiRMfrBQsWSJLi4+OVmJiorVu3\nSpKSkpKcjpswYYIiIyMlSSNHjtS8efP04osvymw2Ky4uToMGDXLUXvxYsnnz5mns2LGqVauWEhMT\n1aFDB6OXBwAAAACoQtwyeEdGRio1NfWy81eau8jX11cjR468Yk1oaKhTwAcAAAAAoKy55aXmAAAA\nAABUFgRvAAAAAAAMRPAGAABVyqZNmzRw4EDFxMQoODhY69atc5pfu3at+vfvrzvuuEPBwcHas2fP\nFc83YMCAUs9zUW5urmJiYhQSEqJffvmlzNYBAKg4CN4AAKBKsVqtatmypZKTk0v9DFar1arY2FiN\nGzfuqp/ROnv2bJnN5ivW/fWvf1XLli1vum8AQMXllg9XAwAAMEpCQoISEhIkSXa7/ZL5hx9+WJKU\nlZVV6vxFu3fv1ty5c/XRRx8pOjq61Jp33nlH+fn5+stf/qLPP/+8DLoHAFREBG8AAIDrdPbsWT31\n1FNKTk5WYGBgqTX79u3Ta6+9ptWrVysjI6N8GwQAuBUuNQcAALhOf//73xUbG6vOnTuXOn/+/HmN\nGDFCL7zwgurXr1/O3QEA3A073gAAANdh3bp1+vbbb/Xpp59etmby5MmKiIjQgw8+KOl/l7Rf6dJ1\nAEDlRfAGAAC4Dt9++60OHz6s5s2bO40PGTJEcXFxWrZsmb777jv99NNPWr16taQLgdtutysqKkoj\nR47U6NGjXdE6AMBFCN4AAACXUdrTyp9++mn179/faaxDhw6aNGmSOnXqJEmaO3euCgsLHfPbtm3T\nX//6V61cuVJhYWHGNg0AcDsEbwAAUKVYrVYdOnTIcdl3Zmamdu/eLX9/fzVs2FAWi0VHjx5Vdna2\n7Ha7Dhw4ILvdrnr16ikoKEiBgYGlPlCtQYMGCg4OliSFhoY6zZ0+fVp2u13h4eGqVauW8YsEALgV\ngjcAAKhS0tLSlJiYKJPJJJPJpEmTJkmSEhMTNW3aNK1bt06jR492zI8YMUKSNHr0aI0aNarUc17t\n876vtQYAUDkRvAEAQJXStm1bZWVlXXa+d+/e6t2793Wd88iRI1f9mlerAQBUXnycGAAAAAAABiJ4\nAwAAAABgIII3AAAAAAAGIngDAAAAAGAgHq4GAAAqpGzLGeUV2l3dRrnx8TLL16PqrBcAKhOCNwAA\nqJB+OVekISt+cnUb5Wbuw83k68FHkgFARcSl5gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAA\nAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4A\nAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI\n4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAA\ngIEI3gAAAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAA\nAAAAGIjgDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjg\nDQAAAACAgQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGIjgDQAAAACA\ngQjeAAAAAAAYiOANAAAAAICBCN4AAAAAABiI4A0AAAAAgIEI3gAAAAAAGMjT1Q2UZu/evVq1apXS\n09NlsViUlJSk1q1bO9WkpqZqw4YNKigoULNmzTR06FDdeuutjvkzZ84oJSVFW7duldlsVlxcnAYO\nHChvb29HTWZmplJSUnTgwAH5+fmpa9eu6tmzZ7mtEwAAAABQ+bnljve5c+fUqFEjDR48uNT5Dz74\nQB9//LGGDh2qyZMnq3r16kpOTlZRUZGj5rXXXtPRo0c1fvx4jR07Vnv37tXs2bMd82fPnlVycrKC\ngoL0j3/8QwMGDNCyZcu0fv16w9cHAAAAAKg63DJ4R0dHq0+fPmrTpk2p82vXrtXDDz+s1q1bKzQ0\nVE899ZRycnK0efNmSVJWVpbS0tL0pz/9SU2aNFGzZs00aNAgfffdd7JYLJKkr7/+WsXFxRo2bJiC\ng4N1zz33qFu3blq9enW5rRMAAAAAUPm5ZfC+kp9//lkWi0V33HGHY8zHx0dNmzbVvn37JEn79++X\nr6+vbrvtNkdNVFSUTCaT9u/fL0nat2+fWrRoIQ8PD0dNq1atdOzYMVmt1nJaDQAAAACgsqtwwfvi\njrWfn5/TuJ+fn2POYrFcMm82m1WzZk1HTV5eXqnn+PXXAACgKiooKND48eMVFxenJk2a6MEHH1Ra\nWppTzf79+zVo0CC1aNFCTZs21R/+8AcdO3ZM0oUrz4KDgxUSEqLg4GCnP2vWrHHFkgAAcCm3fLja\njbDb7TKbr/x7BLvdLpPJVE4dAQBQMY0ZM0b79+/XjBkzVK9ePa1YsUJ9+/bVF198oVtuuUUZGRl6\n6KGH1L9/fyUlJalmzZr66aefHA8wbdiwobZv3+50znfffVezZs1Shw4dXLEkAABcqsIFb39/f0kX\ndqwv/rck5efnq1GjRo6avLw8p+NKSkpUUFDgOMbPz++Smouvf33ea1W7dm3Z7fbrPg7uz5p32tUt\nwEBmDw8FBFz/9zxQWRUWFmrt2rVasWKF7r//fknSnXfeqc8//1zLli3T+PHj9ec//1ndu3fXP//5\nT8dx0dHRTuepW7eu0+vPPvtMvXv3VsOGDcus15wTeVcvqkR4v0Jlwc9WlVtVeq+6nk3dChe869Wr\nJ39/f+3cuVNhYWGSJKvVqv3796tLly6SpIiICBUUFOjQoUOO+7x37twpu92u8PBwR01qaqpKSkoc\nO+VpaWlq0KCBfHx8rruv/Px82Wy2slgi3IxXcbGrW4CBSoqLlZOT4+o2ALdRUFCg4uJinTt3zul7\nw9PTU19++aVOnz6tjz/+WMOGDVO3bt20a9cuhYSE6Omnn3b8O/xbO3bsUFpaml588cUy/X6zV7w7\n5m4K71eoLPjZqnKrSu9VXl5eCgoKuqZat/wXq7CwUBkZGcrIyJAknThxQhkZGTp16pQkqXv37nr/\n/fe1ZcsWHT58WDNmzFDdunUVGxsr6cIlbtHR0Xrrrbd04MAB/fjjj0pJSVG7du0cu9n33nuvPD09\nNXPmTGVlZem7777T2rVr1aNHD5esGQAAd+Dr66uYmBhNnz5dJ06cUElJiVasWKGtW7fq559/1qlT\np1RQUKCZM2eqQ4cOWrx4sbp166YhQ4Zo06ZNpZ5z8eLFioiI0F133VXOqwEAwD245Y53enq6Jk6c\n6Hi9YMECSVJ8fLyGDx+uBx54QOfOndOcOXNUUFCgFi1a6LnnnpOn5/+WM3LkSM2bN08vvviizGaz\n4uLiNGjQIMe8j4+Pxo0bp3nz5mns2LGqVauWEhMTufcMAFDlvf766xo9erRiYmLk6emp22+/XQ8+\n+KB27dqlkpISSVKXLl00ePBgSVJkZKS2bNmid999V3FxcU7nKiws1IcffqhRo0aV+zoAAHAXbhm8\nIyMjlZqaesWa3r17q3fv3ped9/X11ciRI694jtDQUKeADwAALvz7uHz5cp09e1ZnzpxRUFCQhg0b\nppCQEAUEBMjT01NNmzZ1OqZp06b6/vvvLznX6tWrVVhYqIcffri82gcAwO245aXmAADA9WrUqKGg\noCBZLBZ9+eWX6tq1q7y8vNSqVSsdPHjQqTY9PV3BwcGXnGPJkiXq3LmzAgICyqttAADcjlvueAMA\nANf58ssvZbfb1aRJEx06dEgvvfSSwsPDHVeaDRs2TMOHD1dcXJzuueceff755/rss8+0fPlyp/Mc\nOnRImzZt0nvvveeKZQAA4DYI3gAAwEl+fr5efvllZWdny9/fX7///e/1t7/9TR4eHpKkrl27asqU\nKXr99dc1fvx4NWnSRHPmzFHr1q2dzpOamqoGDRqoffv2rlgGAABug+ANAACc9OjR46qf8tGnTx/1\n6dPnijVjx47V2LFjy7I1AAAqJO7xBgAAAADAQARvAAAAAAAMRPAGAAAAAMBABG8AAAAAAAzEw9UA\nAKgkvM4WSGcLXN1GubHXCHR1CwAAXBOCNwAAlcXZAhU+M8TVXZSf6Std3QEAANeES80BAAAAADAQ\nwRsAAAAAAAMRvAEAAAAAMBDBGwAAAAAAAxG8AQAAAAAwEMEbAAAAAAADEbwBAAAAADDQDX+O986d\nO3Xo0CH17NnTMbZhwwYtW7ZMRUVFateunR577DGZzWR7AAAAAEDVdcOpeNmyZcrIyHC8Pnz4sObM\nmaPatWsrMjJSa9eu1apVq8qiRwAAAAAAKqwbDt5Hjx5VkyZNHK+/+uor1ahRQ5MmTdKoUaPUsWNH\nffXVV2XSJAAAAAAAFdUNB+/CwkLVqFHD8Xr79u2Kjo5W9erVJUnh4eE6efLkzXcIAAAAAEAFdsPB\nOzAwUAcPHpQkZWdn68iRI4qKinLMnzlzRl5eXjffIQAAAAAAFdgNP1zt3nvv1fLly5WTk6OsrCz5\n+voqNjbWMZ+enq769euXSZMAAAAAAFRUNxy8//jHP6qoqEjbtm1T4P9r786jvK4L/Y+/ZpiBYWkY\nEdDYVBTGUJTcyCwg80YuZaViuWSSpFlZ/azUzC0vttysW2mbG92bJW5Q6ZVySczIBUVDSQHBBQkV\nYRhlQJnl90fH770TLoDzcZjh8TiHc5zP5/35zvsz5/TuPOf9/Xynb9+cfPLJ6dmzZ5J/7nY//PDD\nOeigg9psogAAANARbXJ4d+nSJZ/4xCfyiU98Yr1zvXr1yiWXXPKmJgYAAACdQZv8ke2VK1fm8ccf\nz9q1a9vi5QAAAKDTeFPhfe+99+ZLX/pSTjrppJx22mlZuHBhkqS+vj5f+9rXcs8997TJJAEAAKCj\n2uTwnj17dr73ve/lbW97W4444ohW56qrq9OnT5/cfvvtb3Z+AAAA0KFtcnhfd911GTFiRM4///yM\nHz9+vfPDhw/P4sWL39TkAAAAoKPb5PB+8skns++++77m+d69e6e+vn5TXx4AAAA6hU0O727dur3u\nh6k988wz6dWr16a+PAAAAHQKmxzeu+yyS2bOnJmmpqb1ztXV1eXWW2/N7rvv/qYmBwAAAB3dJof3\nJz7xiaxYsSJnnHFGbr755iTJAw88kKuuuiqnnnpqkuTwww9vm1kCAABAB1WxqRcOGDAg3/zmNzNl\nypRMnTo1SfL73/8+STJixIh8+tOfTv/+/dtmlgAAANBBbXJ4J8ngwYNz1lln5cUXX8yyZcvS0tKS\nbbbZJtXV1W01PwAAAOjQNjm8ly9fnqqqqvTq1Su9evXKTjvt1Or8yy+/nPr6+vTt2/dNTxIAAAA6\nqk1+xvtzn/tcPvvZz+bPf/7zq56/++6787nPfW6TJwYAAACdwSaHd5JUV1fnoosuypQpU9Lc3NxW\ncwIAAIBO40094/3KJ5v/5je/yRNPPJEvf/nLnu8GAACA/+NN7XgnyYc//OGceeaZWbJkSU4//fQ8\n9thjbTEvAAAA6BTedHgnya677ppvf/vb2WqrrXLOOefk9ttvb4uXBQAAgA7vTb3V/P/aeuutc955\n5+Xyyy/PT3/60wwaNKitXhoAAAA6rDbZ8X5FRUVFPvOZz+Skk07KsmXL2vKlAQAAoEPa5B3vqVOn\nvua5973vfdlrr72ydu3aTX15AAAA6BTa7K3m/+ptb3tb3va2txX18gAAANAhbHB4/+QnP0lZWVlO\nPPHElJeX5yc/+ckbXlNWVpbPfvazb2qCAAAA0JFtcHg//PDDKSsrS3Nzc8rLy/Pwww+/4TVlZWVv\nanIAAADQ0W1weF988cWv+zUAAACwvjZ7xvvpp5/OX//619TV1WXAgAEZN25cevTo0VYvDwAAAB3S\nRoX3jBkzctNNN+X8889PdXV16fjs2bPzgx/8II2NjaVjN910UyZPntxqHAAAAGxpNurveM+ePTvb\nbLNNq5huamrKz3/+85SXl+ezn/1svve97+Woo47K8uXLc/3117f5hAEAAKAj2ajwXrJkSYYNG9bq\n2MMPP5z6+vocfPDBGTduXAYPHpxDDz00++67b+bMmdOmkwUAAICOZqPC+4UXXsjWW2/d6tjcuXOT\nJPvss0+r47W1tVm+fPmbnB4AAAB0bBsV3jU1Namrq2t17JFHHkm3bt2y3XbbtTpeUVGRioo2++w2\nAAAA6JA2KryHDh2amTNnZs2aNUmSp556KgsXLszuu++eLl26tBr79NNPr7c7DgAAAFuajdqSPuKI\nI3LGGWfklFNOyeDBg7No0aIkyUc+8pH1xt57773ZZZdd2maWAAAA0EFt1I73kCFDcvbZZ2fo0KFZ\nuXJlhg0bljPOOCM77rhjq3EPP/xwunbtmn333bdNJwsAAAAdzUY/hF1bW5szzjjjdcfssssuufDC\nCzd5UgAAANBZbNSONwAAALBxhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECB\nhDcAAAAUSHgDAABAgYQ3AAAAFKiivSewKZqbm3P11VfnzjvvTF1dXbbaaquMGzcuhx12WKtxU6dO\nzW233ZbVq1entrY2kyZNyrbbbls6/+KLL+byyy/Pfffdl/Ly8owePTqf+tSnUlVV9VbfEgAAAJ1U\nh9zxnj59em655ZaccMIJ+c///M8cc8wx+d3vfpcZM2a0GjNjxoxMmjQpF1xwQbp165bJkyensbGx\nNOZHP/pRnn766Zx99tk5/fTT8/e//z2/+MUv2uOWAAAA6KQ6ZHjPnz8/e+21V0aNGpW+fftm9OjR\n2W233bJw4cLSmJtuuimHHXZY9tprrwwZMiSf//zns2LFitxzzz1JkiVLluTBBx/MSSedlB133DG1\ntbU5/vjjM2vWrNTV1bXXrQEAANDJdMjwrq2tzUMPPZR//OMfSZLHH388jz76aN75zncmSZ599tnU\n1dVl5MiRpWt69OiRYcOGZf78+UmSBQsWpGfPntlhhx1KY3bbbbeUlZVlwYIFb+HdAAAA0Jl1yGe8\nP/KRj2TNmjX50pe+lPLy8rS0tOTjH/949ttvvyQp7Vj37t271XW9e/cunaurq1vvfHl5eXr16mXH\nG7UpsuoAACAASURBVAAAgDbTIcN71qxZufPOO/OlL30pgwYNyuOPP54pU6akT58+GTNmzGte19LS\nkvLy19/kb2lpSVlZWVtPGQAAgC1UhwzvX/3qV/noRz+afffdN0kyePDgPPfcc5k2bVrGjBmTmpqa\nJMmqVatK/50k9fX12X777ZMkNTU1WbVqVavXbW5uzurVq9fbCd8Q1dXVaWlp2cQ7YnPWsOr59p4C\nBSrv0iV9+tS88UDoAKxXnZv1is7CWtW5bUlr1cZs2HbI8H755ZfXu8mysrJS+Pbv3z81NTWZO3du\ntttuuyRJQ0NDFixYkPHjxydJhg8fntWrV2fx4sWl57znzp2blpaWDBs2bKPnVF9fn3Xr1r2Z22Iz\nVdnU1N5ToEDNTU1ZsWJFe08D2oT1qnOzXtFZWKs6ty1praqsrEy/fv02aGyHDO8999wz119/fbbe\neusMHjw4ixcvzo033pj999+/NOaggw7K9ddfn2233Tb9+/fPVVddla233jp77713kmTgwIEZNWpU\nfv7zn+eEE05IY2NjLr/88uy3336tdskBAADgzeiQ4T1x4sRMnTo1l112Werr67PVVlvlAx/4QA47\n7LDSmEMPPTQvvfRSLrnkkqxevTrveMc78vWvfz0VFf97y6ecckouu+yynH/++SkvL8/o0aNz/PHH\nt8ctAQAA0El1yPCuqqrKcccdl+OOO+51x02YMCETJkx4zfM9e/bMKaec0tbTAwAAgJIO+Xe8AQAA\noKMQ3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4A\nAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDh\nDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAF\nEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAA\nUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0A\nAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLe\nAAAAUCDhDQAAAAUS3gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFAg\n4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAAAFCgivaewKZasWJFrrzyyjzwwAN5\n6aWX8va3vz2f/exnM3To0NKYqVOn5rbbbsvq1atTW1ubSZMmZdttty2df/HFF3P55ZfnvvvuS3l5\neUaPHp1PfepTqaqqao9bAgAAoBPqkDveq1evzllnnZXKysqceeaZ+cEPfpBjjz02vXr1Ko2ZPn16\nZsyYkUmTJuWCCy5It27dMnny5DQ2NpbG/OhHP8rTTz+ds88+O6effnr+/ve/5xe/+EV73BIAAACd\nVIcM7+nTp6dv37456aSTMnTo0PTr1y+77bZb+vfvXxpz00035bDDDstee+2VIUOG5POf/3xWrFiR\ne+65J0myZMmSPPjggznppJOy4447pra2Nscff3xmzZqVurq69ro1AAAAOpkOGd733Xdfdtxxx3z/\n+9/PpEmTctppp+XWW28tnX/22WdTV1eXkSNHlo716NEjw4YNy/z585MkCxYsSM+ePbPDDjuUxuy2\n224pKyvLggUL3rqbAQAAoFPrkM94P/PMM/njH/+YQw45JB/72MeycOHCXHHFFamsrMyYMWNKO9a9\ne/dudV3v3r1L5+rq6tY7X15enl69etnxBgAAoM10yPBuaWnJjjvumI9//ONJku233z5PPfVUbr75\n5owZM+Z1rysvf/1N/paWlpSVlbXpfAEAANhydcjw3mqrrTJw4MBWxwYOHFh6frumpiZJsmrVqtJ/\nJ0l9fX2233770phVq1a1eo3m5uasXr16vZ3wDVFdXZ2WlpaNvo7NX8Oq59t7ChSovEuX9OlT88YD\noQOwXnVu1is6C2tV57YlrVUbs2HbIcO7trY2S5cubXVs6dKl6du3b5Kkf//+qampydy5c7Pddtsl\nSRoaGrJgwYKMHz8+STJ8+PCsXr06ixcvLj3nPXfu3LS0tGTYsGEbPaf6+vqsW7fuzdwWm6nKpqb2\nngIFam5qyooVK9p7GtAmrFedm/WKzsJa1bltSWtVZWVl+vXrt0FjO+SHqx188MFZsGBBpk2blmXL\nluXOO+/Mbbfdlg9+8IOlMQcddFCuv/76zJ49O08++WQuuuiibL311tl7772T/HOHfNSoUfn5z3+e\nhQsX5pFHHsnll1+e/fbbr9UuOQAAALwZHXLHe8cdd8xXvvKV/PrXv851112X/v3751Of+lT222+/\n0phDDz00L730Ui655JKsXr0673jHO/L1r389FRX/e8unnHJKLrvsspx//vkpLy/P6NGjc/zxx7fH\nLQEAANBJdcjwTpI99tgje+yxx+uOmTBhQiZMmPCa53v27JlTTjmlracGAAAAJR3yreYAAADQUQhv\nAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ\n8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACA\nAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAA\nACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAG\nAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJ\nbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAo\nkPAGAACAAglvAAAAKJDwBgAAgAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAA\ngAIJbwAAACiQ8AYAAIACCW8AAAAokPAGAACAAglvAAAAKJDwBgAAgAJVtPcE2sK0adNy1VVX5aCD\nDspxxx2XJFm3bl1++ctf5q9//WvWrVuX3XffPSeccEJ69+5dum758uW55JJLMm/evFRVVWXs2LE5\n6qijUl7u9xEAAAC0jQ5fmAsXLsytt96a7bbbrtXxKVOmZM6cOTn11FNz3nnnZeXKlbnwwgtL55ub\nm/Otb30rzc3NmTx5cj73uc/l9ttvz9VXX/1W3wIAAACdWIcO77Vr1+bHP/5xTjrppPTs2bN0vKGh\nIX/6059y3HHHZcSIEdlhhx1y8skn59FHH83ChQuTJA8++GCWLl2aL3zhCxkyZEhGjRqVI488Mn/4\nwx/S1NTUXrcEAABAJ9Ohw/vSSy/NnnvumV133bXV8UWLFqWpqanV8QEDBqRv376ZP39+kmTBggUZ\nMmRIqqurS2N23333NDQ05KmnnnprbgAAAIBOr8OG91/+8pc88cQTOeqoo9Y7V1dXl4qKivTo0aPV\n8d69e6eurq405v8+750kNTU1pXMAAADQFjrkh6s9//zzmTJlSs4666xUVGz4LbS0tGzQuLKyso2e\nU3V19Qa/Ph1Lw6rn23sKFKi8S5f06VPT3tOANmG96tysV3QW1qrObUtaqzamGztkeC9atCj19fU5\n7bTTSseam5szb968zJgxI2eeeWYaGxvT0NDQate7vr6+tKtdU1OTxx57rNXrvrLT/a874Ruivr4+\n69at25TbYTNX6Zn/Tq25qSkrVqxo72lAm7BedW7WKzoLa1XntiWtVZWVlenXr98Gje2Q4T1y5MhW\nn1CeJBdffHEGDhyYj3zkI+nTp0+6dOmShx56KPvss0+SZOnSpVm+fHmGDx+eJBk+fHimTZuW+vr6\n0nPef/vb39KjR48MGjTorb0hAAAAOq0OGd5VVVXrxXFVVVXe9ra3lY7vv//++eUvf5mePXume/fu\nueKKK1JbW5uddtopSbLbbrtl0KBBueiii3L00Udn5cqVmTp1asaPH79Rb18HAACA19NpC/O4445L\neXl5vv/972fdunUZNWpUPv3pT5fOl5eX57TTTsull16ab3zjG6mqqsrYsWMzYcKEdpw1AAAAnU2n\nCe9zzjmn1deVlZWZOHFiJk6c+JrX9O3bN6effnrRUwMAAGAL1mH/nBgAAAB0BMIbAAAACiS8AQAA\noEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsA\nAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8\nAQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBA\nwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAA\nCiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEA\nAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIb\nAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAok\nvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAAClTR3hPYFNOmTcs999yTpUuXpmvXrhk+fHiOPvroDBgw\noDRm3bp1+eUvf5m//vWvWbduXXbfffeccMIJ6d27d2nM8uXLc8kll2TevHmpqqrK2LFjc9RRR6W8\n3O8jAAAAaBsdsjAfeeSRHHjggZk8eXLOOuusNDU1ZfLkyXn55ZdLY6ZMmZI5c+bk1FNPzXnnnZeV\nK1fmwgsvLJ1vbm7Ot771rTQ3N2fy5Mn53Oc+l9tvvz1XX311e9wSAAAAnVSHDO8zzjgjY8aMyaBB\ngzJkyJCcfPLJWb58eRYtWpQkaWhoyJ/+9Kccd9xxGTFiRHbYYYecfPLJefTRR7Nw4cIkyYMPPpil\nS5fmC1/4QoYMGZJRo0blyCOPzB/+8Ic0NTW15+0BAADQiXTI8P5XDQ0NSZJevXolSRYtWpSmpqbs\nuuuupTEDBgxI3759M3/+/CTJggULMmTIkFRXV5fG7L777mloaMhTTz31Fs4eAACAzqzDh3dLS0um\nTJmSnXfeOYMGDUqS1NXVpaKiIj169Gg1tnfv3qmrqyuN+b/PeydJTU1N6RwAAAC0hQ4f3pdeemmW\nLFmSL37xi284tqWlZYNes6ys7M1OCwAAAJJ00E81f8Vll12WOXPm5Jvf/Gb69OlTOl5TU5PGxsY0\nNDS02vWur68v7WrX1NTksccea/V6r+x0/+tO+Iaorq7e4LCnY2lY9Xx7T4EClXfpkj59atp7GtAm\nrFedm/WKzsJa1bltSWvVxmzYdtjwvuyyyzJ79uyce+656du3b6tzQ4cOTZcuXfLQQw9ln332SZIs\nXbo0y5cvz/Dhw5Mkw4cPz7Rp01JfX196zvtvf/tbevToUXrL+saor6/PunXr3uRdsTmq9GF7nVpz\nU1NWrFjR3tOANmG96tysV3QW1qrObUtaqyorK9OvX78NGtshw/vSSy/NX/7yl3zta19Lt27dSjvV\nPXr0SNeuXdOjR4/sv//++eUvf5mePXume/fuueKKK1JbW5uddtopSbLbbrtl0KBBueiii3L00Udn\n5cqVmTp1asaPH5+Kig75YwEAAGAz1CEL8+abb06SnHvuua2On3zyyRk7dmyS5Ljjjkt5eXm+//3v\nZ926dRk1alQ+/elPl8aWl5fntNNOy6WXXppvfOMbqaqqytixYzNhwoS37D4AAADo/DpkeE+dOvUN\nx1RWVmbixImZOHHia47p27dvTj/99LacGgAAALTS4T/VHAAAADZnwhsAAAAKJLwBAACgQMIbAAAA\nCiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEA\nAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIb\nAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAok\nvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACg\nQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAA\nAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwB\nAACgQMIbAAAACiS8AQAAoEDCGwAAAAokvAEAAKBAwhsAAAAKJLwBAACgQMIbAAAACiS8AQAAoEDC\nGwAAAAokvAEAAKBAwhsAAAAKVNHeE2hvM2bMyO9///vU1dVl++23z/HHH5+ddtqpvacFAABAJ7FF\n73jPmjUr//3f/50JEybku9/9brbbbrtMnjw59fX17T01AAAAOoktOrxvvPHGHHDAARk7dmwGDhyY\nSZMmpVu3bvnTn/7U3lMDAACgk9hiw7uxsTGLFi3KyJEjS8fKysoycuTIzJ8/vx1nBgAAQGeyxYb3\nCy+8kObm5vTu3bvV8d69e6eurq6dZgUAAEBns8V/uNqrKSsr2+hrKir8KDuriqruqdyxtr2n8Zbp\n3q0ytf17tfc03jLdu1amsnLj/zcPmyPrVedmvaKzsFZ1blvSWrUxDVjW0tLSUuBcNluNjY059thj\nc+qpp2avvfYqHb/44ovT0NCQr371q+04OwAAADqLLfat5hUVFRk6dGjmzp1bOtbS0pKHHnootbVb\nzm/g4F9NmTKlvacAsEGsV0BHYK0i2cLfan7wwQfn4osvztChQ7PTTjvlxhtvzEsvvZRx48a199Sg\n3TzzzDPtPQWADWK9AjoCaxXJFh7e7373u/PCCy/k6quvTl1dXbbffvuceeaZqa6ubu+pAQAA0Els\n0eGdJOPHj8/48ePbexoAAAB0UlvsM94AAADwVhDeQCv77bdfe08BYINYr4COwFpFsgX/OTEAAAB4\nK9jxBgAAgAIJbwAAACiQ8AYAAIACCW/YQh155JGZPXt2e08D4HVZq4COwnrF6xHewJs2b968HHnk\nkWloaNig8VOnTs2JJ56YY445Jueff36WLVtW8AwBNm6tuueeezJ58uR8+tOfzpFHHpknnnjiLZgh\nwD9t6HrV1NSUX/3qV/nKV76SY489NieeeGIuuuiirFy58i2aKRtKeANv2sb8cYTp06dnxowZmTRp\nUi644IJ069YtkydPTmNjY4EzBNi4tWrt2rXZeeedc/TRRxc4I4BXt6Hr1UsvvZQnnngihx9+eL77\n3e/mq1/9av7xj3/ku9/9bsEzZGNVtPcEgNfW0tKS3/3ud7n11lvz/PPPp6amJgcccEA++tGP5skn\nn8yUKVMyf/78dOvWLaNHj84nP/nJVFVVla6/7bbbcuONN2bZsmXp1atXRo8enYkTJ673febNm5fz\nzjsvV1xxRXr06JEkefzxx3Paaafl4osvTt++fbN8+fJcdtlleeSRR9LY2Jj+/fvn2GOPzcCBA/PN\nb34zSXL88ccnScaOHZuTTz75Ve/ppptuymGHHZa99torSfL5z38+kyZNyj333JN3v/vdbfrzA94a\nnXGtGjNmTJLkueeea9OfFdC+Ott61aNHj5x55pmtjk2cODFf//rX8/zzz2frrbdus58db47whs3Y\nlVdemT/96U857rjjsvPOO2flypV5+umn8/LLL+eCCy7I8OHD8+1vfzurVq3Kz372s1x++eWlRfmP\nf/xj/uu//ivHHHNMRo0alYaGhjzyyCObPJdLL700TU1NOf/889O1a9csWbIkVVVV6du3b0499dRc\neOGF+eEPf5ju3buna9eur/oazz77bOrq6jJy5MjSsR49emTYsGGZP3++8IYOqrOtVUDntSWsV6tX\nr05ZWVl69uy5yXOj7Qlv2EytXbs2N910U0444YTSzkv//v1TW1ubW265JevWrcvnP//5dO3aNYMG\nDcrEiRPzne98J8ccc0yqq6tz/fXX58Mf/nA++MEPll5z6NChmzyf559/PqNHj86gQYNKc3lFr169\nkiTV1dWl3+q+mrq6uiRJ7969Wx3v3bt36RzQsXTGtQronLaE9WrdunX59a9/nfe85z2tduppf8Ib\nNlNLlixJY2Njdt111/XOLV26NNttt12r337W1tampaUlS5cuTZKsXLnyVa/dVAceeGAuueSSPPjg\ngxk5cmTe9a53ZciQIa85/s4778wvfvGLJElZWVnOOOOMlJe/+sdKtLS0vOY5YPPWGdeqnXfeuc3m\nA2w+Ovt61dTUlO9///spKyvLCSec0GbzpG0Ib9hMvd5bilpaWlJWVrZJ176aV3utpqamVl/vv//+\nGTVqVO6///48+OCDmT59ej75yU+2+q3v/7XXXntl2LBhpa/79OlT+oTNVatWpaampnSuvr4+22+/\n/UbNGdg8dMa1CuicOvN69Up0P//88zn77LPtdm+GbDHBZurtb397unbtmrlz5653btCgQXn88cfz\n8ssvl4498sgjKS8vz4ABA1JVVZV+/fq96rWvprq6Okla/emJxYsXrzeuT58+OeCAA3LqqafmkEMO\nya233pokqaj45+/wmpubS2OrqqqyzTbblP5VVlamf//+qampaTWvhoaGLFiwILW1tRs0V2Dz0hnX\nKqBz6qzr1SvR/eyzz+bss88uvU2dzYvwhs1UZWVlDj300Fx55ZW544478swzz2TBggW57bbb8t73\nvjcVFRW56KKL8tRTT+Whhx7KFVdckTFjxpQW+iOOOCI33HBDbrrppixbtiyLFi3KjBkzXvV7bbvt\nttl6661zzTXXZNmyZbn//vtz4403thozZcqUPPjgg3n22WezaNGiPPzww6Vnkvr27ZuysrLcd999\nqa+vz9q1a1/zvg466KBcf/31mT17dp588slcdNFF2XrrrbP33nu30U8OeCt11rXqxRdfzOOPP56n\nnnoqSfL000/n8ccf93kU0IF1xvWqubk5F154YRYvXpwvfOELaWxsTF1dXerq6vyp1s1Ml3PPPffc\n9p4E8OpGjBiR5ubm3HDDDfntb3+bBx54IIMGDcouu+ySUaNG5d57783VV1+de++9N3vuuWc+9alP\nlX5Duv3226e6ujozZszItGnTMnv27NTU1GTUqFFJkmuvvTb77bdfBgwYkPLy8gwbNiy33357pk2b\nlueeey4f/ehH89e//jUHH3xwevTokfvvvz8zZszI9OnTc9ddd2X48OE5/vjj07Vr13Tv3j3l5eWZ\nPn16rr322qxYseI1Q3rnnXfOSy+9lGuvvTYzZsxInz598sUvfrH0f2pAx9MZ16pZs2blW9/6Vv7y\nl78kSe6+++7ccsst6d69e0aMGPHW/GCBNtfZ1qtX/iTZmjVrcvPNN+eGG24o/Rs5cmT69ev3lv58\neW1lLRv619kBAACAjeat5gAAAFAg4Q0AAAAFEt4AAABQIOENAAAABRLeAAAAUCDhDQAAAAUS3gAA\nAFAg4Q0AAAAFEt4AAABQIOENALymc889N+edd157TwMAOrSK9p4AALC+Z555Jr/97W8zd+7crFix\nIhUVFRkyZEj23XffHHDAAenatetbMo+ysrJCX3/atGkZNGhQ9t5770K/DwC0J+ENAJuZ+++/Pz/4\nwQ9SWVmZMWPGZMiQIWlsbMwjjzySK6+8MkuWLMlnPvOZ9p5mm5g2bVre9a53CW8AOjXhDQCbkWef\nfTY//OEP079//5x99tnp3bt36dwHPvCBPPPMM7n//vvbcYabv3Xr1qWioqLw3XoA2FDCGwA2I7/9\n7W+zdu3anHTSSa2i+xXbbLNNDjzwwCRJc3Nzrr/++sycOTMrVqxITU1N3vve9+bwww9PRcWG/V/8\nHXfckRkzZuSpp54qvZ39sMMOy2677faq42+//fb89Kc/zcUXX5y+ffuWjs+bNy/nnXdezjnnnIwY\nMSJJsmzZsvzqV7/K/Pnzs3r16lRXV6e2tjYnnnhiunfvniOPPDJJMnPmzMycOTNJMnbs2Jx88slJ\nkhUrVuSqq67KnDlz0tDQkG233TYHH3xw9t9///W+7xe/+MU8+eSTmTlzZlauXJnLL7883bp1y/XX\nX58777wzy5cvT1VVVQYOHJgjjjgiI0eO3KCfDwC0BeENAJuR+++/P9tss02GDRv2hmN/+tOf5o47\n7si+++6bD33oQ1m4cGGmTZuWJUuW5Ctf+cobXn/NNdfk2muvTW1tbY488shUVFRkwYIFeeihh14z\nvDdUY2Nj/v3f/z1NTU058MADU1NTkxUrVuT+++/P6tWr071793zhC1/IT3/60wwbNiwHHHBAkn/+\nYiFJVq1alTPPPDPl5eU58MADU11dnTlz5uTnP/951q5dm4MOOqjV97vuuutSUVGRD33oQ2lsbExF\nRUWuvvrqTJ8+PQcccEB23HHHrFmzJo899lgWL14svAF4SwlvANhMrFmzJitWrNig552feOKJ/QGH\n3AAABkxJREFU3HHHHXn/+99fet77Ax/4QKqrq/P73/8+8+bNK+08v5ply5bluuuuy+jRo/P//t//\nKx3/4Ac/+OZvJMmSJUvy3HPP5dRTT80+++xTOn7YYYeV/vs973lPfvGLX6R///55z3ve0+r63/zm\nN2lpacl3v/vd9OzZM0lywAEH5Ic//GGuueaa/Nu//VsqKytL49etW5fvfOc7rXb658yZkz322COT\nJk1qk3sCgE3lz4kBwGZizZo1SZKqqqo3HDtnzpwkySGHHNLq+Ctfv9Fz4Pfcc09aWlpy+OGHb8pU\n31CPHj2SJA888EBefvnljb7+7rvvzp577pnm5ua88MILpX+77757Ghoasnjx4lbjx40bt97b63v2\n7JklS5Zk2bJlm34jANAG7HgDwGaie/fuSZK1a9e+4djnnnsu5eXl2XbbbVsdr6mpSY8ePfLcc88l\nSRoaGlqFb0VFRXr16pVnn3025eXlGThwYBvewf/q379/DjnkkNxwww3585//nJ133jl77bVX3vve\n95ai/LXU19enoaEht9xyS2655ZZXHbNq1apWX/fr12+9MRMmTMh//Md/5Itf/GIGDx6cUaNGlT4l\nHgDeSsIbADYT3bt3z1ZbbZUnn3zyDce2tLRs0GtOmTKl9MFlSTJixIicc845G3z9v3qtTwpvbm5e\n79ixxx6bcePG5d57783f/va3XHHFFZk+fXomT56cPn36vOb3eOW13vve92bcuHGvOuZf4/nV/q75\nO97xjvz4xz8uff/bbrstN954YyZNmtTqA9oAoGjCGwA2I3vssUduvfXWLFiw4HU/YK1///5pbm7O\nsmXLMmDAgNLxVatWpaGhobQDfOihh2bMmDGl8688L73tttumubk5S5YsyXbbbbfB83vl+tWrV7f6\nVPNnn332VccPHjw4gwcPzsc+9rHMnz8/Z511Vm6++ebSJ5q/WshXV1enqqoqzc3N2XXXXTd4bq81\n33HjxmXcuHF56aWXcvbZZ+eaa64R3gC8pTzjDQCbkUMPPTTdunXLz372s/XeTp3880PR/ud//ifv\nfOc7kyQ33nhjq/O///3vk/wz4JNk4MCB2XXXXUv/dthhhyTJ3nvvnbKyslx77bUbtfv9ylvb//73\nv5eONTc359Zbb201bs2aNevtgg8ePDhlZWVZt25d6Vi3bt3S0NDQalx5eXlGjx6du+++O0899dR6\nc6ivr9+gub744outvu7WrVu23XbbNDY2btD1ANBW7HgDwGZkm222ySmnnJIf/vCH+fKXv1x6Jrmx\nsTGPPvpo7rrrrrzvfe/LQQcdlLFjx+aWW27J6tWrM2LEiCxYsCB33HFH9tlnn9f9RPPknwH9sY99\nLNddd13OPvvsjB49OhUVFXnsscfSp0+ffOITn3jV6wYNGpThw4fnyiuvzAsvvJBevXpl1qxZ60X2\nQw89lMsvvzzvete78va3vz3Nzc2ZOXNmunTpkne9612lcUOHDs3cuXNzww03pE+fPunfv3922mmn\nHH300Zk3b16+/vWv5/3vf38GDRqUF198MYsWLcrDDz+cyy677A1/ll/+8pezyy67ZOjQoenVq1cW\nLlyYu+66q/R30AHgrdLl3HPPPbe9JwEA/K8BAwbk3e9+d1avXp0HHnggs2bNyrx589K1a9d86EMf\nykc/+tGUl5dnzz33TJcuXTJnzpzcddddeeGFFzJ+/PhMnDgx5eVv/Ka2XXbZJf369cv8+fMza9as\nPProo6msrMy4cePSv3//JMnMmTNTVlaWsWPHlq7bdddd8+STT+bOO+/MokWLMnr06Lz//e/PHXfc\nkXHjxqVfv36prKzMypUrM3fu3Nx999159NFH069fv3zmM5/JzjvvXHqtoUOHZvHixfnzn/+cWbNm\npampKXvvvXeqqqrynve8J2vWrMns2bNz11135cknn0yPHj1y8MEHl3bun3vuucycOTP77rtvBg0a\n1Or+mpqasnDhwsyePTv33Xdf1qxZk0MOOSQTJkx4zWfVAaAIZS2b+ukqAAAAwBvyjDcAAAAUSHgD\nAABAgYQ3AAAAFEh4AwAAQIGENwAAABRIeAMAAECBhDcAAAAUSHgDAABAgYQ3AAAAFEh4AwAAQIGE\nNwAAABRIeAMAAECBhDcAAAAU6P8DBst//nMVDToAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a80b790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ** Plot top terms for each cluster and the cluster sizes **\n",
    "\n",
    "n_terms = input_with_default_int('Number of top terms', 10)\n",
    "\n",
    "# --> top terms\n",
    "plot_cluster_top_terms(doc_term_data['doc_term_matrix'], doc_term_data['term_labels'], n_terms, coclust_specMod_model)\n",
    "# --> cluster sizes\n",
    "plot_cluster_sizes(coclust_specMod_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of random initialization: [default: 1] \n"
     ]
    }
   ],
   "source": [
    "# ** Compute co-clustering with the CoclustInfo approach **\n",
    "\n",
    "n_clusters = best_coclustMod_model.n_clusters\n",
    "n_rand_init = input_with_default_int('Number of random initialization', 1)\n",
    "# Perform co-clustering\n",
    "coclust_info_model = CoclustInfo(n_row_clusters = n_clusters, n_col_clusters = n_clusters,\n",
    "                                 n_init = n_rand_init, random_state = 0)\n",
    "coclust_info_model.fit(doc_term_data['doc_term_matrix'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========\n",
      "(Best) Modularity co-clustering\n",
      "-----\n",
      "NMI: 0.902094144579\n",
      "ARI: 0.937922418426\n",
      "ACCURACY: 0.978925726034\n",
      "==========\n",
      "Spectral Modularity co-clustering\n",
      "-----\n",
      "NMI: 0.913719371893\n",
      "ARI: 0.941247834466\n",
      "ACCURACY: 0.979439732717\n",
      "==========\n",
      "Info co-clustering\n",
      "-----\n",
      "CRITERION: 0.368259482727\n",
      "NMI: 0.930673152976\n",
      "ARI: 0.959306989875\n",
      "ACCURACY: 0.986378822925\n"
     ]
    }
   ],
   "source": [
    "# ** Compare clustering quality measure for coClustMod, coClustSpecMod and info **\n",
    "\n",
    "true_row_labels = doc_term_data['doc_labels']\n",
    "n_clusters = best_coclustMod_model.n_clusters\n",
    "\n",
    "def print_NMI_and_ARI(true_row_labels, predicted_row_labels):\n",
    "    nmi_ = nmi(true_row_labels, predicted_row_labels)\n",
    "    ari_ = ari(true_row_labels, predicted_row_labels)\n",
    "    print(\"NMI: {}\\nARI: {}\".format(nmi_, ari_))\n",
    "\n",
    "## Evaluate the results for (Best) Modularity co-clustering\n",
    "print(10*'=')\n",
    "print(\"(Best) Modularity co-clustering\")\n",
    "print(5*'-')\n",
    "#print(\"CRITERION: %s\" % best_coclustMod_model.criterion)\n",
    "predicted_row_labels = best_coclustMod_model.row_labels_\n",
    "print_NMI_and_ARI(true_row_labels, predicted_row_labels)\n",
    "print_accuracy = accuracy(true_row_labels, predicted_row_labels)\n",
    "print(\"ACCURACY: %s\" % print_accuracy)\n",
    "            \n",
    "## Evaluate the results for Spectral Modularity co-clustering\n",
    "print(10*'=')\n",
    "print(\"Spectral Modularity co-clustering\")\n",
    "print(5*'-')\n",
    "#print(\"CRITERION: %s\" % coclust_specMod_model.criterion)\n",
    "predicted_row_labels = coclust_specMod_model.row_labels_\n",
    "print_NMI_and_ARI(true_row_labels, predicted_row_labels)\n",
    "print_accuracy = accuracy(true_row_labels, predicted_row_labels)\n",
    "print(\"ACCURACY: %s\" % print_accuracy)\n",
    "      \n",
    "## Evaluate the results for Info co-clustering\n",
    "print(10*'=')\n",
    "print(\"Info co-clustering\")\n",
    "print(5*'-')\n",
    "print(\"CRITERION: %s\" % coclust_info_model.criterion)\n",
    "predicted_row_labels = coclust_info_model.row_labels_\n",
    "print_NMI_and_ARI(true_row_labels, predicted_row_labels)\n",
    "print_accuracy = accuracy(true_row_labels, predicted_row_labels)\n",
    "print(\"ACCURACY: %s\" % print_accuracy)"
   ]
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    "editable": true
   },
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   "source": []
  }
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